WEANLING NEEDS AND THE NEXT PREGNANCY AMONG THE IRAQW OF TANZANIA
DISSERTATION
Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
in the Graduate School of The Ohio State University
By
Crystal L. Patil, M.A.
*****
The Ohio State University 2004
Dissertation Committee: Approved by Dr. Ivy L. Pike, Advisor
Dr. Douglas E. Crews ______Adviser Dr. Kristen J. Gremillion Department of Anthropology
ABSTRACT
The reproductive process is characteristically biocultural and evolutionary. A woman concurrently manages her own biosocial needs and the needs of those dependent on her while pregnant. This negotiation process takes place in a specific social and ecological context which is the source of constraints and buffering mechanisms. The birth of a child creates an atmosphere of social change for a mother, her most recently weaned child, and the newborn. This study was carried out from September 2001 to November 2002 among the Iraqw, a group of Southern Cushitic speakers residing in northern Tanzania. A sample 45 women were selected to assess the impact of increasing fertility on young family development in the contest of social change. This longitudinal study examined biological, social, economic and demographic variation in relation to pregnancy, birth, child growth, and health. The primary objectives of this research were: 1) to identify if there are changes in child growth rates or morbidity throughout the birth transition; 2) to identify if changes in maternal body composition are reflected in the body composition of her children; and 3) to determine whether a mother’s social environment is associated with outcomes of pregnancy and child growth and morbidity. Results from this initial study have raised many questions. There is no clear finding that the birth of a sibling creates a vulnerable period of time for the index child. However, there are protective behaviors that indicate that mothers (and newborns) are nutritionally buffered during this time and that mothers nutritionally buffer some children under certain circumstances. There is ample evidence to suggest that social networks are critical to health and well being and that shifts in gender ideology in this younger generation may confound negative effects. Future research will focus on the details of social networks and the effects of shifting gender ideology in the context of reproduction and child caretaking.
iii
Dedicated to my “Little M & Ms”
and
Baraka
iv
ACKNOWLEDGMENTS
First and foremost I must thank the people of Haydom area and especially the women who shared a year of their lives with me and more. Thank you for tolerating the measurements, laughing at my ridiculous questions, and forgiving my poor Kiswahili and even worse Kiiraqw! I am grateful and humbled. Each person/family we had contact with has changed some portion of my life and the life of my family forever. Valentina and Eli – I could not have done any of this without you! Even learning to drive in the bush and greetings would have been impossible without your guidance. I am grateful to Deodatis Amedeus Masay who taught us that “the impossible is possible in Tanzania”. Evalina, Teckla, Helena, Flora, Kaptolina, and Paschalina – I thank you. Mama Neema and Katarina – without you life would have been difficult for us. At the University of Dar es Salaam, I thank Dr. Lawi, Dr. Tungaraza, Dr. Frida Tungaraza, Dr. Kaaya, and Joe Lugalla for professional support. I must thank Dada Veron – Veronica! You saved us literally and figuratively so many times. Your care, concern, generosity, love, warmth, happiness, sense of pride, ethics and everything about you made us feel like we had a family member in Haydom everyday. The “non-local locals” in both hemispheres deserve special thanks. Mwalimu Deo –you are patient and caring and shared so much. Katherine – we only knew each other in Africa! Thank you. You taught me that it is ok if I didn’t “get it” and encouraged me not to be too hard on myself. Thank you for teaching me that field work is a slow process and that it will take years and years AND that it is ok. Katherine, Sasha, Fabiola, Wilder, and Colletta – the respites in Mbulu were so nice.
v Barbara (Barabara) – you shared our language and customs, but most importantly your M & Ms! Thank you for helping us survive the first few months and laughing with us (not at us) when we did not understand. You have a special place in our hearts. Dr. Olsen and Mama Kari – you deserve your own chapter of praises – we can only say “Thank You” and it is not enough. Dr. Bjorg Olsen – your support over the years has been wonderful. Thank for encouraging this project and in the midst of your own dissertation taking the time to answer my emails with comprehensive and thoughtful responses. When I think about this project and the total of the last ten years at Ohio State, I am surprised by all of the people I can credit with influencing some aspect of my graduate career. At Bloomsbury University, my professors introduced me to anthropology and how to “teach” anthropology. Special thanks Tom Aleto, Dee Ann Wymer, Dave Minderhout and Bob Reeder. The encouragement and opportunities provided by P. Pacheco got the ball rolling and I gratefully acknowledge is support through muddled times. At Ohio State I acknowledge Dr. Gremillion, for being more than patient with me as I maneuvered my way through different aspects of anthropological thought. You knew I genuinely needed to “find people”. I thank you for your guidance and great advice. Dr. Crews - your human variation class changed my whole direction. My Ph.D. advisor, Dr. Ivy Pike – I knew when we met that our paths were meant to cross. You quickly got me up to speed and never doubted that I would “catch up”. You taught me that theory should drive research but never told me “what to do”. Thank you for providing the examples that allowed me to learn. I value your intelligence and thank you for introducing me to East Africa. We will always be connected by those nights laughing “in the bush”. I have more than benefited from your guidance, encouragement, and friendship. You have profoundly influenced the way I think and view the world. “Lead by example” are the first words that come to mind when I think of Cathy Rakowski. Your advice and encouragement are absolutely priceless and I had opportunities to work with some of the most amazing people through WID.
vi Alyson Young, thank you for those long phone calls and instant messaging sessions that got me through tough times. I promise to partially repay as you continue on your own similar journey. I will always remember x-mas on the 4th of July! Betsy Abrams – your unending enthusiasm kept me going and your visions of the future keep me going. Special thanks to Ann Biersteker, Brittany Eckleberry, Tori Saneda, Bram Tucker, Jarrod Burks, Craig and Erica Keener, and Linda Whitman. My family in the Philadelphia area – thanks so much for understanding the unexplainable – you accepted that I HAD to go to graduate school and HAD to go to Africa even if it meant leaving you all behind. Your phone calls and visits in desperate times refueled me. I especially thank you for making me see that I should be proud. Betty and Popat and Vikas– this Ph.D. is partially yours. You all earned it. I think it stands for Profound (and heartfelt) Dedication to family and education. You made the combination of the two possible! The fact that we never had to worry about our children made life so much easier. You tolerated the ups and downs of the process with such grace. I also appreciate that you wanted to share a part of Africa with us and did. Vikas – you are my best friend and make my life complete; I can not thank you enough for your unending and unconditional support. I am fairly certain that without you this project never would have happened. You gave me the confidence to plan it and see it through. Not many people would pick up and move across the world twice or work double-overtime so that I could keep writing. I can’t express how much I appreciate what you do and why you do it. You are an old soul and that is only one explanation for your ability to tolerate so much (including the unofficial “Lilith Fairs” you have willingly attended). Mo Cheeks, Jimmy Jackson, mariposa, light refraction, off! – need I say more??? Of course, but that sums up so much that only you would understand. And that’s the point – only YOU would understand.
vii VITA
1993 ………………………………………B.A. Anthropology, Bloomsburg University of Pennsylvania
1996 ………………………………………M.A. Anthropology, The Ohio State University
1996 – 2001 ………………………………Graduate Teaching Associate, The Ohio State University
2003 – 2004 ………………………………Presidential Fellow, The Ohio State University
2004 ………………………………………Postdoctoral Fellow in Medical Anthropology, Washington University at St. Louis
PUBLICATIONS
Pike, I.L. and C.L. Patil. Understanding women's burdens: preliminary findings on psychosocial health among Datoga and Iraqw women of northern Tanzania. Accepted to Culture Medicine and Psychiatry, May 2004.
Patil, C.L. 2003. Sociality and Health among the Iraqw of North-central Tanzania. American Journal of Human Biology 15(2): 278.
Pike, I.L., C.L. Patil and A.G. Young. 2003. Examining women’s psychosocial stress among three subsistence populations of East Africa. American Journal of Human Biology 15(2): 279.
Patil, C.L., I.L. Pike, S.R. Williams, and L.B. Sansbury. 2000. The developmental niche, household dynamics, and early childhood nutritional status for Turkana of Kenya. American Journal of Human Biology 12 (2): 269.
viii FIELDS OF STUDY
Major Field: Anthropology
Specializations: Biocultural Anthropology International Health Anthropology of Reproduction, Breastfeeding, and Childcare
ix TABLE OF CONTENTS
Page Abstract …………………………………………………………………………….. ii Dedication ………………………………………………………………………….. iv Acknowledgments …..……………………………………………………………... v Vita …………………………………………………………………………………. viii List of Tables ………………………………………………………………………. xiv List of Figures ……………………………………………………………………… xix
CHAPTER 1. INTRODUCTION AND THEORETICAL BACKGROUND ... 1
1.1 Introduction .………………....………………………………………..…… 1 1.2 Theoretical Background .…………………………………………...... 4 1.2.1 Reproductive Ecology ……………………..……………………..... 5 1.2.2 Behavioral Ecology ………………………..……………………..... 9 1.2.3 Childhood …………………..……………………………..……….. 10 1.2.4 Evolutionary Theory ……………………………..………………... 10 1.2.5 Life History Theory ………………………..…………………….... 11 1.2.6 Theories of Childhood ……………………..……………………… 12 1.2.7 Psychology of Caretaking ………………………..………………... 15 1.3 Framework for the Research ………………………..……………………... 16
CHAPTER 2. THE STUDY POPULATION …………………………………... 19 2.1 Introduction to the Area …………………………………………………… 19 2.2 An Abbreviated History …………………………………………………… 21 2.3 Population Growth ………………………………………………………… 22 2.4 Physical Features and Environment ……………………………………….. 24 2.5 Introduction to the Iraqw ………………………………………………….. 25 2.5.1 A Brief History ………………………………………………………….. 25
x 2.5.2 Political and Economic Change …………………………………… 27 2.5.3 Physical Environment ……………………………………………... 28 2.6 Health ……………………………………………………………………… 30 2.6.1 A Brief History of Medical Care ………………………………….. 30 2.6.2 Health Concerns …………………………………………………… 31 2.7 Culture and Ideology ………………………………………………... 35
CHAPTER 3. METHODOLOGY …..………………………….……………….. 45
3.1 Introduction ………………………………………………………………... 45 3.2 History of the Project ……………………………………………………… 45 3.3 Sample Selection and Criteria 46 ……………………………………………… 3.4 Data Collection ……………………………………………………………. 47 3.5 Data Analysis ……………………………………………………………… 54
CHAPTER 4. RESULTS I: 58 DESCRIPTIVE DEMOGRAPHIC AND SOCIAL STATISTICS ……..……...
4.1 Introduction ……………………………………………………………….. 58 4.2 Demographic and Social Composition ……………………………………. 58 4.2.1 Household Sociodemographics ……………………………………. 58 4.2.2 Household Economics …………………………………………….. 61 4.2.2.1 Husbands’ Employment Status ………………………….. 61 4.2.2.2 Women’s Employment Status …………………………... 61 4.2.2.3 Animal Husbandry ………………………………………. 62 4.2.2.4 Wealth Status ……………………………………………. 63 4.3 Maternal Biodemographics ………………………………………………... 66 4.3.1 Marriage Patterns ………………………………………………….. 66 4.3.2 Reproductive History ……………………………………………… 66
xi 4.3.2.1 Pregnancy Sickness ……………………………………… 67 4.3.3 Maternal Anthropometry ………………………………………….. 68 4.3.3.1 Pregnancy Weight Gain …………………………………. 68 4.3.3.2 Body Mass Index ………………………………………... 69 4.3.3.3 Summed Skinfold Measures …………………………….. 71 4.3.3.4 Body Fat ………………………………………………… 73 4.4 Index Children …………………………………………………………….. 75 4.4.1 Biodemographics ………………………………………………….. 75 4.4.2 Breastfeeding ……………………………………………………… 76 4.4.2.1 Weaning …………………………………………………. 76 4.4.2.2 Lactational Status at Conception of Sibling ….…………. 76 4.4.3 Growth …………………………………………………………….. 78 4.4.3.1 Height and Weight of Sample by Age …………………... 78 4.4.3.2 Height-for-age …………………………………………… 81 4.4.3.3 Weight-for-age …………………………………………... 83 4.4.3.4 Weight-for-height ……………………………………….. 85 4.4.3.5 Arm Circumference ……………………………………... 87 4.4.3.6 Calf Circumference ……………………………………… 90 4.4.4 Socioemotional Patterns 92 4.4.5 Summary 93 4.5 Newborn/Infant Anthropometry …………………………………………... 94 4.5.1 Birth Outcome ……………………………………………………... 94 4.5.1.1 Gestational Age ………………………………………….. 95 4.5.1.2 Maternal Biosocial Predictors of Birth Outcome ……….. 96 4.5.2 Newborn/Infant Growth …………………………………………… 98 4.5.2.1 Length-for-age …………………………………………... 98 4.5.2.2 Weight-for-age …………………………………………... 100 4.5.2.3 Weight-for-length ……………………………………….. 102
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CHAPTER 5 – RESULTS II: ASPECTS OF THE DEVELOPMENTAL 105 NICHE
5.1 Introduction ………………………………………………………………... 105 5.2 Aspects of the Model ……………………………………………………… 106 5.2.1 Psychology of the Caretaker ………………………………………. 106 5.2.1.1 Pregnancy Sickness and Birth Outcome ………………… 106 5.2.1.2 Anxiety and Depression …………………………………. 107 5.2.1.3 Major Worries …………………………………………… 113 5.2.1.4 Major Worries and Birth Outcome ……………………… 118 5.2.2 Social Support ……………………………………………………... 121 5.2.3 Maternal Morbidity ……………………………………………….. 122 5.2.4 Growing and Maturing Child ……………………………………… 124 5.2.4.1 Temperament ……………………………………………. 124
CHAPTER 6: RESULTS III: THE BIRTH TRANSITION ………………….. 130
6.1 Introduction ……………………………………………………………….. 130 6.2 Index Child and Growth Change through Birth Transition ……………….. 130 6.2.1 Rate of Growth ……………………………………………………. 134 6.2.2 Morbidity ………………………………………………………….. 138 6.2.2.1 Index Children …………………………………………... 138 6.2.2.2 Newborns/Infants ……………………………………….. 143
CHAPTER 7: RESULTS IV: REPRODUCTION AND SOCIAL CONTEXT 152 152 7.1 Introduction ……………………………………………………………….. 152 7.2 Cattle and Milk ……………………………………………………………. 152 7.2.1 Maternal …………………………………………………………… 153 7.2.2 Children …………………………………………………………… 153
xiii 7.2.2.1 Index Children …………………………………………... 153 7.2.2.2 Newborns/Infants ……………………………………….. 155 7.3 Social Relations …………………………………………………………… 157 7.3.1 Marital communication/decision-making 157 …………………………………………………... 7.3.1.1 Maternal …………………………………………………. 157 7.3.1.2 Index Children …………………………………………... 158 7.3.1.3 Newborns/Infants ……………………………………….. 159 7.3.2 Vurugu/fujo 160 …………………………………………………………… 7.3.2.1 Maternal: Biodemographic Associations ………………... 160 7.3.2.2 Index Children …………………………………………... 184 7.3.2.3 Newborns/Infants ……………………………………….. 186
CHAPTER 8: DISCUSSION ……………………………………………………. 181
8.1 Introduction ...……………………………………………………………… 181 8.2 Historical context .………………………………………………………..... 182 8.3 Birth Transition, Developmental Niche, and Health Outcomes …………... 186 186 8.3.1 Will there be a change in anthropometric measures, especially in the rates of weight and height gain by the older sibling (index child) when comparing rates of change in the months before birth to rates in the months after birth? ………………………………... 189 8.3.2 Are changes in body composition of the mother reflected in the newborn and/or index child through the birth transition? ……….. 190 8.3.3 Is maternal social status, assessed by her support network, psychosocial stress levels, autonomy, and household composition, associated with outcome variables for any of the three members of the triad (mother, index child, and newborn? ....
8.4 Theoretical implications ...………………………………………………… 192 8.4.1 Parent-Offspring Conflict 192
xiv 8.4.2 Future Directions 193 8.4.2.1 Vurugu/Fujo 193 8.4.2.2 Domestic Violence 194 8.4.1 Attitudes/Norms …………………………………………………… 196 8.4.2 Alcohol/Poverty/Isolation/Male Dominance/Decision-Making …... 197 8.4.3 Child Abuse ……………………………………………………….. 198 8.5 Summary …………………………………………………………………... 203
Bibliography ………………….……………………………..…………………….. 205
Appendix A – Research Clearance and Tanzanian Support of Research ...…... 232
Appendix B – IRB ……………………………..………………………………….. 238 Appendix C – Examples of Survey Questions…………………………………… 240
Appendix D – Swahili Version of Hopkins Symptom Checklist – 25 ……...... 249
Appendix E – Codes for Statistical Analysis ……………………………………. 253
Appendix F – Average Recumbent Length and Weight of Boys and Girls in Sample from Birth through age 74 months ……………………... 264
Appendix G – Pearson and Spearmen Correlation Coefficients for Select Groups of Variables ...... 267
xv LIST OF TABLES
Table Page 2.1 Causes of death for children under age five attending Haydom Hospital in 2001 and 2002 …………………..………………………………….……... 35
3.1 Number of triads measured in each month ………………………………... 51
4.1 Distribution of sample by geographic area ..………………………….…… 51
4.2 Household sociodemographic data …………………………………..……. 57
4.3 Employment status of fathers/husbands and mothers/women ..…….…….. 59
4.4 Average number of animals owned ……………………………….….…… 60
4.5 Animals on loan ……………………………………………….…………... 61
4.6 Number and percentage of triads living in each category of housing .…..... 62
4.7 Crude wealth categories …………………………………………………… 62
4.8 Pattern of marriage for 44 participants .…………………………………… 65
4.9 Anthropometric and biodemographic data for mothers 66 ………………….....
4.10 List of pregnancy sickness symptoms ..…………………………………… 67
4.11 Average weight gain and average daily rate of change in 2nd and 3rd trimesters of pregnancy and in months post partum 67 ..………………………
4.12 Average BMI .……………………………………………………………... 68
4.13 Results of Mann-Whitney U tests for differences in BMI based on availability of helpers ……………………………………………………… 69
xvi
4.14 Average summed skinfolds ..………………………………………………. 70
4.15 Results of Mann-Whitney U tests for differences in summed skinfold measures by presence of a household helper ………………………………… 71
4.16 Average body fat percentage .…………………………………………...…… 72
4.17 Results of Mann-Whitney U tests for differences in bioimpedence by the presence or absence of household help ………………………………………. 73
4.18 Average age (months) of index children at birth of sibling ..……………...…. 71
4.19 Average age at weaning (months) for index children ..………………………. 72
4.20 Number and percentage of mothers lactating at various points across the birth transition ..…………………………………………………………….... 75
4.21 Average months of lactation into pregnancy by sex of index child ………..... 76
4.22 Results of Mann-Whitney U tests for differences in age of weaning by reliability of mother\-in-law (help) …………………………………………... 76
4.23 Results of Mann-Whitney U tests for differences in birth interval by reliability of mother-in-law …………………………………………………... 77
4.24 Changes in MUAC and calf circumference for index child over birth transition .……………………………………………………………...……... 87
4.25 Results of Mann-Whitney U tests for differences in socioemotional patterns for index children …………………………………………………………….. 91
4.26 Results of Mann-Whitney U tests for differences in socioemotional patterns by sex ………………………………………………………………………… 92
4.27 Birth outcome measures ..………………………………………………...... 94
4.28 Anthropometric data for newborns suspected of being premature ..…………. 95
xvii
4.29 Regression equations predicting birth weight from maternal nutritional status 97
4.30 Results of Mann-Whitney U tests for differences in weight-for-height scores by presence of household helper ……………………………………………... 104
5.1 Results of Mann-Whitney U test statistic testing for differences in birth weight by symptoms experienced during pregnancy ..…………………...... 107
5.2 Mean HSCL-25 scores by parity and gravidity .……………………………... 108
5.3 Regression models for effects of HSCL – 25 on anthropometric measures …. 109
5.4 Mean HSCL – 25 scores by employment status of mother ..………………… 110
5.5 Mean HSCL – 25 scores by mothers’ employment status …………………… 110
5.6 Results of Mann-Whitney U tests for differences in mean HSCL – 25 scores by mothers’ collapsed categories of employment status …………………….. 111
5.7 Average birth weight by mothers’ employment status ………………………. 111
5.8 Results of Mann-Whitney U tests for differences in birth weight by mothers’ employment status …………………………………………………………… 112
5.9 Mean HSCL-25 scores by employment status of husband/father ..………….. 112
5.10 Mean HSCL-25 scores by working status of husband/father .…………...... 112
5.11 Kruskal-Wallis one way ANOVA for HSCL – 25 by husbands’ employment status …………………………………………………………………………. 113
5.12 Mean HSCL-25 scores by sub-groups of women based on their daily worries 114
5.13 Principle components analysis for subscales of the HSCL – 25 ………..…… 116
5.14 Significant worries associated with each subscale created in principles components analysis ……………………………………………………….... 117
xviii
5.15 Mann-Whitney U tests for differences in birth weight by mothers’ worries … 119
5.16 Statistically significant results for differences in birth outcome measures by mothers’ worries ……………………………………………………………... 120
5.17 Summary of members on mother’s list of those she can depend on ………… 121
5.18 Mean number of people on free lists and seen in the last month ...…………... 122
5.19 Results of Mann-Whitney U tests for differences in summed HSCL – 25 scores by names on social network …………………………………………... 122
5.20 Number and percentage of women reporting illness in any give month throughout the birth transition …………………………………………...... 123
5.21 Types of illness experienced by mothers before and after birth of newborns .. 124
5.22 Maternal categories of index child temperament ………………………...... 124
5.23 Categorization of index child’s well being in the first month after birth of sibling ………………………………………………………………………... 125
5.24 Temperament category used in a two way frequency table by index child’s adjustment to newborn …………………………………………...... 127
5.25 Collapsed temperament category used in a two way frequency table by index child’s adjustment to newborn ……………………………………………….. 129
6.1 Rate of weight and stature change throughout the birth transition …………... 134
6.2 Comparisons of z-scores for ratio of weight gain for index children by adjustment category ……………………………………………………...... 135
6.3 Number and percentage of index children ill throughout the birth transition .. 139
6.4 Maternal reports of types of illness experienced by index children and newborns/infants ……………………………………………………………... 140
xix
6.5 Number and percentage of newborns ill ..………………………………...….. 143
6.6 Month of supplementation for newborns and return to work for mother ……. 145
7.1 Results of Mann-Whitney U tests for biosocial differences for women who worry about cattle and milk ………………………………………...... 153
7.2 Results of Mann-Whitney U tests for growth differences in index children by worry about cattle ……………………………………………………………. 154
7.3 Results of Mann-Whitney U tests for growth differences in index children by worry about milk ……………………………………………………...…….... 155
7.4 Results of Mann-Whitney U tests for growth differences in newborns/infants by worry about cattle ………………………………………………………… 156
7.5 Results of Mann-Whitney U tests for growth differences in index children by worry about milk ………………………………………………….………..... 157
7.6 Results of Mann-Whitney U tests for biosocial differences among mothers by worry about marital communication/decision-making ……..…………….. 158
7.7 Results of Mann-Whitney U tests for growth differences in index children by worry about marital communication/decision-making ………………………. 159 . 7.8 Results of Mann-Whitney U tests for growth differences in newborns/infants by worry about marital communication/decision-making .…………………... 160
7.9 Results of Mann-Whitney U tests for differences in biosocial factors by worry about vurugu/fujo …..…………………………………...... 161
7.10 Results of Mann-Whitney U tests for differences in biosocial factors by worry about domestic violence ………………………………………………. 162
7.11 Information on individual women in a domestic violence situation …………. 163
xx
7.12 Results of linear regression models for predicting birth weight by violence category…………………………………………...... 164
7.13 CDC reference data by vurugu/fujo for index children before birth of sibling 165
7.14 CDC reference data by vurugu/fujo for index child after birth of sibling ..….. 166
7.15 CDC reference data by vurugu/fujo for newborns birth to age 3 months ..…... 169
7.16 A comparison of birth weights from women who work for money or brew beer and their worries of violence ………………….……………...... 171
xxi LIST OF FIGURES
Figure Page 1.1 Model of relationships and theoretical underpinnings of research project .. 3
1.2 Components of the birth interval showing that often reproductive events which are treated independently may overlap ………………………….… 6
2.1 Distribution of languages in Tanzania and study area …………..……….. 20
2.2 Regions of Tanzania: Arusha and Manyara Regions ..…………………… 21
2.3 Growth rates reported from the 2002 National Census, Tanzania ……….. 23
2.4 Elevation map of Tanzania showing some natural features ……………… 24
2.5 Former Arusha Region with Babati, Hanang, Karatu, and Mbulu districts labeled ………………………………………………………………….…. 26
2.6 View of Mt. Hanang and the Rift Wall ...……………………………….... 29
2.7 Medical Director, Dr. O.H. Evjen Olsen ……………………………….… 30
2.8 Distribution of stable malaria in Tanzania ……………………………..… 32
2.9 Live births at Haydom Hospital in 2002 by sex ……………………….…. 34
2.10 Zebu cow’s hump …………………………………………………….…... 36
2.11 Typical shop ……………………………………………………………… 37
2.12 Haydom market …………………………………………………………... 37
2.13 Primary school students in Haydom ……………………………………... 43
3.1 Father helping researcher measure index child …………………………... 50
4.1 Variation in Types of Housing ….…………………………………….….. 64
xxii 4.2 Recumbent length (cm) of all children by age and sex ……………..……. 78
4.3 Weight (kg) of all children by age and sex ……………………………….. 79
4.4 Height-for-age for index children by monthly measure ………………….. 81
4.5 Weight-for-age for index children by monthly measure …………………. 83
4.6 Weight-for-height for index children by monthly measure ………………. 85
4.7 Monthly changes in MUAC for index children ………………………...… 88
4.8 Monthly changes in calf circumference for index children …………….… 90
4.9 Length-for-age for newborns …………………………………………...… 98
4.10 Weight-for-age for newborns/infants……………………………………... 101
4.11 Weight-for-length for newborns/infants …………………………….……. 103
6.1 Height-for-age for index children throughout birth transition …………… 131
6.2 Weight-for-age for index children throughout birth transition …………… 132
6.3 Weight-for-height for index children throughout the birth transition ……. 133
6.4 Weight-for-height by adjustment category for index child ……………..... 137
6.5 Mean duration of illness for index children and newborns/infants ………. 142
6.6 Change in body composition for the triad ………………………………... 147
6.7 Weight-for-height for boys by adjustment ……………………………….. 150
6.8 Weight-for-height for girls by adjustment ……………………………….. 151
7.1 Height-for-age by domestic violence for index children ………………..... 174
7.2 Weight-for-age by domestic violence for index children ……………...... 175
xxiii 7.3 Weight-for-height by domestic violence for index children ……………... 176
7.4 Height-for-age by domestic violence for newborns …………………...... 178
7.5 Weight-for-age by domestic violence for newborns ……………………... 179
7.6 Weight-for-height by domestic violence for newborns ………………….. 180
8.1 Ariel view of Haydom Lutheran Hospital and Haydom town …………… 185
xxiv CHAPTER 1
INTRODUCTION AND THEORETICAL BACKGROUND
1.1 Introduction
The reproductive process is characteristically biocultural. A woman concurrently manages her own biosocial needs and the needs of those dependent on her while pregnant. The negotiation process takes place in a specific social and ecological context. This context is the source of constraints and buffering mechanisms. The birth of a child creates an atmosphere of social change for a mother, her formerly youngest child, hereafter referred to as the index child, and the newborn. This dissertation focuses on biocultural aspects of reproduction while considering evolutionary explanations linked to mammalian, primate, and human history and was carried out among a high fertility, agro- pastoral population of Southern-Cushitic speakers in northern Tanzania. The focus of this research is the three most interdependent individuals in a household, collectively referred to as the triad in this dissertation – a mother, the index child, and a newborn. The main objectives of this project are 1) to assess whether morbidity and body composition changes are affected by such a social change; 2) to focus on the household as the developmental niche for the index child to assess whether the psychosocial state of the mother and the socio-emotional responses of the index child are related to health and growth measures; and 3) to investigate buffering strategies employed as women negotiate their own needs in conjunction with the needs of at least their two most dependent children. In line with these objectives, the following are major questions addressed:
1 1. Will there be a change in anthropometric measures, especially in the rates of growth by the older sibling (index child) throughout the birth transition?
2. Are changes in body composition of the mother reflected in the newborn and/or index child throughout the birth transition?
3. Is maternal social status, assessed by her support network, psychosocial stress levels, autonomy, and household composition, associated with outcome variables for any of the three members of the triad (mother, index child, and newborn)?
A review of the literature provides insight on dynamic aspects of the reproductive process with respect to the interactions of these three interdependent individuals – a mother, the previously youngest child (index) and the fetus/newborn,– or, collectively, the triad. In classical evolutionary theory it is assumed that a parent will allocate investment to maximize the number of surviving offspring (Trivers 1972) and it is assumed that offspring are active agents in this process. As such, it is proposed that conflict may arise as each individual attempts to maximize their own reproductive success (Trivers 1974). The theoretical goal of this research project was to focus on the overlap of lactation and pregnancy as a source of parent-offspring conflict and as an avenue to discuss maternal investment in living offspring while considering future reproductive potential. In addition to this theoretical interest, reproduction is treated as a social phenomenon that affects health and well-being. A select review of several bodies of literature is presented to discuss reproduction over the course of pregnancy, birth, and presence of a newborn in the household, or the birth transition. I attempt to examine the birth transition in its socioecological context through which the proximate determinants of nutrition, energy balance, and disease are mediated and influence the triad’s health outcomes and, ultimately, reproductive success (Figure 1.1).
2
Growing/Maturing Child
Biosocial Transition from youngest (infraindividual/individal) child to older sibling Developmental Niche
Physical Psychology of Setting Caretakers Household size Age/Parity Composition Reproductive Status Modes of Production Social network/integration
3 Customs of Care Wealth Marital/Family interactions
Social Ecology (household) Reproductive Transition Allocation Rules Evolution: Age at weaning macroenvironment Sibling Rivalry species/population Parental Investment morbidity/mortality patterns Sociality Current vs. Future Reproduction Life History Parameters
Figure 1.1. Model of relationships and theoretical underpinnings of this research project (Modified after Harkness and Super 1994).
3 1.2 Theoretical Background In order to understand the physiology of the reproductive process today, consideration of various domains of past selective pressures is needed to explain why certain relationships exist (Ellison 2001). As an example, Ellison (2001) has pointed out that the relationship between breastfeeding and ovulation suppression was initially explored and explained from evolutionary perspectives by Howell (1979) and Konner and Worthman (1980). Their work triggered a field of research called reproductive ecology which focuses on ecological influences on the reproductive system in an evolutionary perspective. A hallmark characteristic of mammalian reproduction is the production of milk as the offspring’s only dietary source for a given period of time. This research focuses on factors that relate to a few of the mammalian life history parameters surrounding lactation and the relationship of these factors to other maternal effects (Mather and Jinks 1971): age at weaning (parent-offspring conflict), birth spacing (sibling-sibling competition), current versus future maternal investment, and social relationships. Breastfeeding, especially in poorer countries, is significantly linked to child survival and health; its direct and indirect effects on morbidity and mortality are recognized (Stuart-Macadam and Dettwyler 1995). Cunningham reviews both the short- and long-term protection afforded by breastfeeding. He focuses on the benefits of protection from gastrointestinal and respiratory disease in infancy but also outlines associations later in life including diabetes, cancers, and allergies occurring throughout the lifespan (1995). Breastfeeding, as major component of mammalian maternal investment, and weaning have been examined in light of evolutionary theory. Selective pressures acting in the last 100,000 years on breastfeeding through child mortality are described in the review by McDade and Worthman (1998), and researchers not only focus on these pressures but also the flexibility built into this process allowing for modern populations to thrive in local social and ecological settings (Lee 1996; McDade 2001). For example, some research on weaning shows that under certain circumstances maternal investment strategies are predictable based on the child’s risk for morbidity and mortality. Bereczkei assigned Hungarian infants of primiparous mothers into categories
4 based on the child’s reproductive value or its “own expected fitness” (2001:197). Infants were assigned risk categories of “high” and “low” depending on their birth weight. He found that the child’s probability of survival predicted patterns of breastfeeding. Infants were breast-fed for short durations if they were high risk and those in the lower risk category were breastfed for longer durations. 1.2.1 Reproductive Ecology Complementary to evolutionary theory, this research is informed by reproductive ecology which emphasizes the importance of ecological conditions on the reproductive process and from a biocultural perspective is broadly defined to include socio-cultural, socio-economic, and behavioral variables. Most reproductive ecology research targets females because they are considered the limiting factor in reproduction (Wood 1994, cf. Bentley et al. 1993, Campbell et al. 1995); but in context, women must contend with gender disparities in politics, economics, and culture that may disadvantage them compared to men. The effects of poverty and poor nutrition tend to affect women before children and men (Fee and Krieger 1994; Koblinsky et al. 1993; Leslie 1991; UNICEF 2001). However, research on male reproductive effort and strategies has been addressed in more recent literature and shows that social circumstances influence male reproductive efforts and strategies as well (Bribiescas 2001; Campbell et al. 1995; Hill and Hurtado 1996). For heuristic purposes, research on reproduction addresses the physiological phases of the reproductive process as independent yet interconnected events – ovulation, conception, pregnancy, lactational amenorrhea (breastfeeding), weaning, and menopause (e.g., Bongaarts and Potter 1983; Wood 1994, Ellison 2001). Typically this research is unidirectional in perspective (e.g., mother’s perspective, child’s perspective, fetus/newborn’s perspective). However, the reproductive process is more complex and there is a need to better understand interactions on this process. For example, women in non-contracepting populations routinely identify the next pregnancy as the reason for weaning the previous child (e.g., Almedom and de Waal 1990; Hrdy 1999; Bohler and Bergstrom 1996; Bracher et al. 1982; Cantrelle and Leridon 1971; Dahl 1988; Dettwyler 1992; Devereux 1969; DHS 1996; Gray 1992; Guthrie et al.
5 1983; Hill and Hurtado 1996; Huffman et al. 1980; Kilbride and Kilbride 1990; Merchant et al. 1990; Oliveros et al. 1999; Omari and Kitilia 1976; Pakrasi and Manna 1989; Popkin et al. 1993; Wood 1994). Thus, a successful conception has an impact on the health and well-being of at least three individuals which disproportionately relates their survival and fitness depending on the timing of conception, reproductive behaviors, and culturally specific caretaking practices associated with pregnancy, birth, and the post- partum period (Jakobsen et al. 2003; Merchant et al. 1990; Bohler and Bergstrom 1995; Panter-Brick 1991; Siega-Riz and Adair 1993) (Figure 1.2)
Conception Birth
Pregnancy Lactation
Components of Birth Interval
Figure 1.2. Components of the birth interval showing that often reproductive events which are treated independently may also overlap.
There is an abundance of literature describing breastfeeding patterns and its implications for a woman’s reproductive span including her nutrition, her reproductive health, birth spacing, and child morbidity and mortality. The purpose of this research is to consider the effects of weaning and breastfeeding in the immediate post partum period and to focus on social changes affecting reproductive effort, not only directed toward the newborn, but also including the index child and mother as a result of her increased parity.
6 The role of breastfeeding in reproductive effort (especially in natural-fertility population), is three-fold: nutritional, immunological, and to delay conception. Indeed, breastfeeding behavior has the most profound effect on variation of total fertility rates and child survival in the first six months of life (Gray 1981; Holland 1987; Wood 1994). While breastfeeding, the mother and child are physiologically interdependent; this affects their health, nutrition, development, and psychological well-being (Ellison 2001; Stuart-Macadam and Dettwyler 1995). In developed and developing countries alike, the positive effects of breastfeeding on health and survival are unquestionable (Stuart- Macadam and Dettwyler 1995; Walker 1994). In the first few days of breastfeeding before full milk production occurs, or lactogenesis stage II, a child receives colostrum which is rich in maternal antibodies, especially IgA and IgG. The milk is high in protein and low in fat and lactose. The colostrum has several benefits in addition to meeting nutritional needs. It helps to mature the digestive tract because bacteria are introduced and hormones are delivered which, in turn, promote maturation and development (Wood 1994). This early period of lactation is likely a critical period in newborn development and associated with long-term effects (Lucas 1998; Stuart-Macadam and Dettwyler 1995); it is suggested that post-partum nutrition can have effects not only on current growth and development but also the long-term health outcomes of mothers and their offspring such as decreasing risk of cancer, liver disease, and atherosclerosis (Lucas 1998; Micozzi 1995). Breastfeeding provides protection from diarrhea and infectious disease via maternal antibodies which are together responsible for 43% of child deaths world-wide (Molbeck et al 1994; Popkin et al. 1986; Stuart-Macadam and Dettwyler 1995; UNICEF 1991; Zeitlin 1995). A child’s chances of survival increase with breastfeeding because of passive immunity, decreased exposure to pathogens, and the nutritional quality of breast milk (Popkin 1986). The mother produces antibodies that are specific to her (presumably their) environment which she then passes on to the newborn via breast milk. At a time when the child’s own immune system is immature, until approximately age five, breastfeeding enhances survival and reduces the amount of time and energy a newborn/infant must devote to recovering from infectious disease. In addition to being
7 the sole food supply and source of antibodies, breastfeeding itself protects a newborn by preventing pregnancy in the immediate post-partum through mechanisms of ovulation suppression or lactational amenorrhea (Bonte and van Balen 1969; Habicht et al. 1985; Huffman 1980; Tracer 1996; Vitzhum 1989; Wood 1994). Demographic literature focusing on child survival identifies short birth intervals as a risk factor for mortality and morbidity for the newborn, the mother, and previous child (e.g., Boerma and Bicego 1991; Blurton-Jones 1986; DaVanzo et al. 1983, Hobcraft et al. 1983; Hobcraft et al. 1985; Huffman and Martin 1994; Janowitz et al. 1981; Knodel and Kinter 1977, Majumder et al. 1997; Palloni et al. 1986, Palloni and Millman1986; Palloni and Tenda 1986; Thapa et al. 1988). The direct role of lactation on ovulation suppression and as a birth-spacing mechanism is now a well established fact with implications for mother and her children (Gray 1994; Huffman et al 1980; Habicht et al. 1985; Konner and Worthman 1980; Leridon 1993; Lindstrom and Berhanu 1999; McNeilly 1993; Simondon et al. 2001; Vitzthum 1989; Wood 1994). In natural-fertility populations breastfeeding duration and infant mortality are interconnected. A mediating variable between breastfeeding and mortality is often the weaning process. The weaning process begins with the first nutritional supplementation and ends with complete cessation of breastfeeding (Gray 1992, 1996; Vitzthum 1989). Importantly, breastfeeding behavior and the effects of ovulation suppression show great variation both within and between populations and neither have been modeled adequately (Ellison et al. 1997; Lee 1996; Wood 1994) It is suggested that exclusive breastfeeding provides all the needed nutritional requirements in the first four to six months of life (World Health Organization 2001). The nutritional and immunological benefits of breastfeeding can continue as long as the child is breastfeeding and can provide immunological benefits, especially since a child’s own immune system is immature until approximately age five (Molbeck et al. 1994; Stuart- Macadam and Dettwyler 1995; Zeitlin 1995). Regardless of the child’s age at weaning, the biological switch from passive immunity to active immunity is characterized by increased morbidity (Defo 1997; Molbeck 1994). Among human populations, a five-year duration of breastfeeding would coincide with maturation of the immune system; but
8 rarely does this occur, even in contracepting populations (Dettwyler 1995). After approximately four to six months, an infant’s diet must be supplemented because breast milk alone can no longer fulfill nutritional requirements of the infant; however, the type and timing of the introduction of weaning foods varies greatly from population to population. Over time, dietary supplements, infant behavior, and maternal activity change suckling patterns, which, in turn lead to maternal hormonal changes that initiate a return to ovulation at which time fecundity, the biological capacity to conceive, returns (Ellison 1990, 2001). The cessation of breastfeeding, or the final stage of weaning, is not only about access to breast milk, but may involve behavioral changes for the mother and the weaning child which, as will be discussed in the next section, has been the focus of study for several generations. 1.2.2 Behavioral Ecology Fouts and Hewlett (2001) provide an excellent overview of the conceptual history of the study of weaning; the following summary is based on their historical overview of weaning in anthropological thought. Psychoanalytical and attachment theory have greatly influenced anthropological research on feeding practices and child development. Psychoanalysts define weaning as an important milestone in development with breastfeeding and weaning as part of Freud’s “oral stage”. Denial of the breast was described and assumed to be traumatic for children. Bowlby (1958, 1969) and Ainsworth (1963, 1967) used aspects of psychoanalytical theory to justify their research on the importance of attachment as a survival mechanism for securing successful social relations. Anthropologists built on the work of these psychologists and applied it to their research questions. As Fouts and Hewlett (2001) point out, anthropologists in the culture and personality school of thought included aspects of breastfeeding and weaning in their descriptions because of the importance such stages presumably had on adult personality and ultimately personality of the culture (e.g., Benedict 1934, Kardiner 1947; Mead 1935). Research in the post-culture and personality school, has similarly focused on weaning as a difficulty in childhood (e.g., LeVine and LeVine 1966; Shostak 1976).
9 1.2.3 Childhood: Childhood is a developmental stage defined as exclusive to humans (Bogin 1988, 2001). Childhood actually has many definitions and can be defined biologically, developmentally, and/or chronologically. In addition, childhood takes place in a unique physical, social, and psychological setting. One biological definition of childhood is that is begins at weaning; thus focusing on weaning, a life history parameter, as a nutritional transition from infancy to childhood. The median age at weaning for humans is 36 months (Dettwyler 1995); thus, based on this definition, it can be said that childhood begins at 36 months. Upon closer inspection, it may be that food security that determines the most appropriate ages for the introduction of non-breast milk foods. For example, a dichotomy based on availability of food sources shows that population averages are influenced by food security and access to weaning foods (Bogin 1998). Lee et al. (1991) show that the average age at weaning differs for “food-enhanced” and “food limited” societies by at least 27 months. Therefore, a definition based on age at weaning may not be appropriate for all populations. However, a definition of childhood by changes in weight gain proves interesting. Lee et al. (1991) show that although the “food-enhanced” and “food limited” societies differ in age at weaning, the children are similar in weight at the time of weaning; children are about 2.7 times their birth weight. A demographic definition reveals that being under the age of five means that this segment of the population is at highest risk for morbidity and mortality; thereby offering another useful parameter for assessing risk and defining childhood based on biological vulnerability. As Wiley and Pike (1999) point out, the cultural system itself can define and reinforce such stages; it is through caretaking practices that these points of biological and social maturation can define categories of sub-adults (Gray 1996; Sellen 2001). 1.2.4 Evolutionary Theory Evolutionary theorists were also influenced by psychological research on weaning and childhood. Trivers’ (1972, 1974) classic works on conflicts in reproductive effort laid the groundwork for research on the evolutionary consequences of parental investment (e.g., Clutton-Brock 1991). Researchers focused on weaning as an example of parent-offspring conflict which was acted out through parental caretaking and
10 offspring demands; the assumption was that evolutionary conflict can be seen as behavioral conflict (Bateson 1994); and research on parent-offspring conflict has since been carried out among many species (e.g., Clutton-Brock 1991) including baboons (Altman 1980), chimpanzees (Clark 1977; Goodall 1986), and orangutans (1977), and humans (e.g., Fouts 2003, Hill and Hurtado 1996). Parent-offspring conflict (POC) has received a great deal of attention by zoologists, evolutionary biologists, anthropologists among others. Initially research focused on the importance of sex differences in reproductive behavior and which then led interests on behavioral aspects of parental care (Bateman 1948; Clutton-Brock 1991; Williams 1966; Trivers 1972). Trivers places importance on costs of parental care and its effect on ability to care for all offspring. This complements Clutton-Brocks definition of parental care which focuses on parental behaviors that increase the probability of fitness (1991). Among humans, parental caretaking is fundamental for infants and children to survive and thrive, and variation in childcare practices may have significant consequences for the survival of the mother and her offspring (Bogin 2001; Huffman and Martin 1994; Konner 1981). 1.2.5 Life History Theory: The use of parental investment today is much less restrictive than that implied in the above ideas and is often relied upon by researchers focusing on life history as a branch of evolutionary theory (Hill and Hurtado 1996; McDade 2003; Peacock 1991; Pike 1996). Life history is an approach used to identify evolutionary reasons for explaining species level fertility and mortality patterns based on the allocation of limited energetic resources (Stearns 1992; Morbeck et al. 1997). Researchers have also attempted to assess population level variation in life history parameters to explain variation in fitness among individuals (Charnov 1993; Chisholm 1997; Hill and Hurtado 1996). Life history theory primarily focuses on the allocation of energy among competing demands throughout the various stages of the life cycle (Stearns 1992). A basic premise is that energy for one purpose cannot be used for another purpose. A concept focused on by life history researchers is trade-offs, or, changes in the allocation
11 of energy and time which ultimately constrain the simultaneous evolution of two or more traits (Stearns 1992; Hurtado et al. 1992). In other words, if two traits are competing for limited resources, life history theory allows for explanation of this competition as costs in terms of fitness. Although a very active area of research, applications of life history theory for population level (within species) explanations are yet to be done successfully; partially because life history research does not address mechanisms that allow individuals to buffer themselves over the life course, or bend these allocation rules (Panter-Brick and Worthman 1999; Worthman 2000). To address this shortcoming, it is necessary to incorporate mediating variables, such as the dynamics of social relationships and multitasking behaviors (i.e., overlapping uses of time and energy) into life history models (Panter-Brick and Worthman 1999). For example, humans have out-competed other hominoids by raising multiple dependent and immature offspring successfully (Lancaster and Lancaster 1983, 1987). Lancaster and Lancaster calculated that one out of two human children live to adulthood where as primates and group-hunting carnivores have only 10 – 30% reaching maturity (Lancaster and Lancaster 1983; 1987). This success is probably due to significant changes in the life-cycle characteristics (e.g., childhood and adolescence) and through caretaking behavior changes including male caretaking and alloparenting (Bogin and Smith 1996; Lancaster and Lancaster 1983, 1987). In 100,000 years, human life histories have changed such that the population has grown to over 6 billion from a population of probably no more than 10,000 (Bogin 2001; Hrdy 1999). Buffering mechanisms through social relationships may be critical components that allow modern humans to raise several dependent children concurrently and successfully. Humans are the only hominoid in which male parenting effort must be considered because their investment is substantial compared to that of non-human primates (Muller and Wrangham 2001). Human males divide their energies between parenting effort and mating effort whereas other hominoid species primarily focus on mating effort (Trivers 1972; Muller and Wrangham 2001). This component of human reproductive strategies may have contributed to greater fitness among humans as compared to non-human primates; hence human populations continue to grow rather than continue at replacement levels (or less).
12 1.2.6 Theories of Childhood Parenting strategies are primarily social. Our primate counterparts do not have as much social flexibility and this behavioral component of reproductive effort may be a limiting factor in non-human primate reproductive strategies. The average birth interval for chimpanzees and orangutans is 6 and 8 years respectively as compared to 3 years for the humans (Galdikas and Wood 1990; Goodall 1986; Morbeck et al. 1997; Nishida et al. 1990). One cost of such strategies for humans may be maternal reliance on others or increasing dependence on sociality in successful childrearing (Bowlby 1982; Fox 1967). Reproductive effort and strategies are characterized by maternal and paternal care, not to the exclusion of alloparents (Bogin 2001; Hrdy 1999; Ivey 1993; Daly and Wilson 1983; Trivers 1985). Behavioral flexibility through an increased reliance on others provides human mothers with opportunities to modulate reproductive effort given the dependency of multiple immature offspring. An overview of the birth interval given the information on breastfeeding and ovulation suppression is needed to understand where the costs of these strategies play out. As stated earlier, breastfeeding and ovulation suppression are interconnected and it is well-established that the hormone prolactin has an important role in this process (Gray 1992; Howie and McNeilly 1982; Lunn 1992; Tyson and Perez 1974; Wood et al. 1985; Stallings et al. 1998; Worthman 1993). Since total fertility rates are primarily determined by the length of lactational amenorrhea, there is no doubt that cultural practices will affect breastfeeding patterns that likely control this aspect of the reproductive system. Shorter birth intervals can interfere with the health and well being of the mother, previous child and the fetus/newborn. For breastfeeding mothers in Cameroon, short birth intervals were especially detrimental when the mother quit breastfeeding as a result of the next pregnancy. Those infants were at higher risk for mortality (Defo 1997). In other regions, birth intervals of less than two years increased risk for mortality for both children in the sequence and the mother (Huttly et al. 1992; St. George et al. 2000). It is not uncommon for a woman to be lactating one child while conceiving the next child (Merchant et al. 1990) (Figure 1.1). The outcomes of overlapping
13 reproductive events for each individual are variable and modified by at least two major less proximate conditions: environment and social relationships. Based on western standards of dietary intake – which it should be noted, may not be representative - the metabolic (anabolic and catabolic) demands of pregnancy are great, requiring approximately 55,000 kcal or 4.7 kcal/g of weight gain during pregnancy (Durnin 1987). The daily energetic requirements of lactation average out to between 500 - 625 kcal/day (Vellegia and Ellison 2001; Dewey 1997). The demands of concurrent pregnancy and breastfeeding, which is essentially metabolizing for three rather than two, have not been assessed; but are most likely more energetically demanding and perhaps associated with risk of morbidity and mortality for a mother, her breastfeeding child, and the fetus/newborn (Ellison 2001). However, it should be noted, that breastfeeding into the third trimester is not common and it is during the 3rd trimester that the energetic costs of pregnancy are greatest. Among mammals with gestation and lactation of similar duration, the overlap of pregnancy and lactation is a greater energetic burden. The energetic costs of lactation are said to be most demanding in late lactation for many mammals (Forsum et al. 1992; Johnson et al. 2001; Millar 1977, Oswald and McClure 1987). Among humans, gestation and lactation duration are different and the energetic demands of lactation peak over the first six months and decline thereafter; thus the overlap of pregnancy and lactation is not likely as energetically demanding as is seen in smaller mammals with gestation and lactation intervals of similar duration. Among Norway rats, resting metabolism was 10% greater for rats both pregnant and lactating as compared to rats only lactating (Oswald and McClure 1987). In addition to the increased metabolic costs, breast milk composition may be altered (Marquis et al. 2003). Dairy cow research indicates that milking in late pregnancy actually reduces milk production (Remond et al. 1992). The metabolic costs of the overlap of pregnancy and lactation have not been calculated for humans but several studies point out that there are physiological consequences to this overlap for both mothers and children. Siega-Riz and Adair found that lactation into the third trimester negatively affected weight gain among Filipino women (1993). Others have found that breast milk composition is different; they report
14 that concentrations of lactose and lysozyme in colostrum were different from mothers who breastfed into pregnancy and that intake of IgA at 1 month post partum was significantly lower for newborns in the overlapping group different (Marquis et al. 2002, 2003). In addition, Marquis et al. also report that the overlap of pregnancy and breastfeeding was significantly associated with milk volume from 68 Peruvian women who lactated into the 3rd trimester (2004). Perhaps the decreased volume of milk production also explains why the newborns at one month of age gained approximately 125 grams less than infants of mothers who did not breastfeed into the third trimester (Marquis et al. 2002). Marquis et al.s’ study among Peruvian women (n = 727) was the first to show that growth of the successive infant may be compromised as a result of overlapping reproductive events (2002). One study from India shows that women with overlapping reproductive events have lower body weights than those who do not have overlapping events (Ramachandran 1987). These data suggest that overlapping reproductive events may have negative effects not only for the fetus/newborn but also for the mother. Repeated cycles of pregnancy and lactation are associated with maternal depletion of fat stores and nutrients; repeated cycles increase the likelihood of overlapping reproductive events (Merchant et al. 1990; Winkvist et al 1992, 2002). Conclusions from these sources should be approached with caution because no research has been done to address mediating relationships for this overlap nor has research been done in affluent societies (Winkvist et al. 2003). 1.2.7 Psychology of Caretaking Recently documented links between psychosocial stress and disease suggest new insights into the determinants of health (Ader et al. 1991; Black 1994; Flinn 1995, 1999). Researchers suggest that stress via cortisol release, increases susceptibility to diseases (Finn and England 1997; Saplosky 1999). Traumatic events, such as divorce, change of residence, loss of a job or social support are associated with elevated levels of cortisol. Through reduced immunocompetence, persistent stress can divert resources from important health functions (Cohen 1993, House et al. 1988; Mairer et al. 1994). However, from an evolutionary perspective, it is argued that suppression of the immune system does not necessarily confer an adaptive advantage. One researcher, among others,
15 notes that stress may actually enhance immune function by activating the antigen- specific, cell-mediated, or delayed type hypersensitivity (DHT) in the skin (Dhabhar 1996). Thus, the relationship of the stress and the immune system remain interesting yet poorly understood. The birth transition is treated as a normal, but stressful, transition for members of the triad. Weaning and birth are biological and social transitions for a mother, the index child, and newborn (e.g., Hrdy 1999; Dahl 1988; Devereux 1969; Hill and Hurtado 1996; Lerer 1998; Omari and Kitilia 1976; Pakrasi and Manna 1989) and, as such, provide an ideal situation in which to examine associations among stresses, behavior, and physiological responses. In addition to parent-offspring conflict, sibling-sibling competition has also been described among many species. Trivers discusses temper tantrums as an example of the active role the child takes in trying to manipulate parental investment (Trivers 1974). Evidence of sibling-sibling competition may result as a mother turns more of her attention to the newborn at the expense of the weanling. Daly and Wilson suggest that psychological manipulation of parents by the child can be a means to encourage more investment (1988). As Ivey (1993) and Levins and Lewontin (1985) point out, assuming such behaviors as psychological manipulation and tantrums resulted from natural selection can be criticized because these behaviors may simply be a by-product of the situation and have nothing to do with natural selection. Indeed, defining honest signaling would be the best approach because it is these behaviors on which natural selection would have acted rather than all positive or negatively categorized and observed behaviors. However, parental investment strategies are sensitive to socio-ecological context but difficult to quantify (Clutton-Brock 1991; Hrdy 1999) . This sensitivity means that hypotheses may still be generated although causality is not assumed (Hill and Hurtado 1996; Lack 1968; Ivey 1993; Trivers 1972). 1.3 Framework for the Research Women in many societies are primarily responsible for household survival as they employ various coping strategies to buffer the household from perturbation (Bentley et al. 1991, 1999; Dufour et al. 1997; Messer 1997). The dynamic interaction of environment, social relationships, and cultural values can be referred to as the
16 developmental niche especially when viewed from the child’s perspective (Harkness and Super 1994) (Figure 1.2). The developmental niche is a tool providing a framework to test hypotheses about physical/social setting, customs of childcare, and psychological states of the caretaker(s) on child well being. Although definitions of a household vary, in this research a household is an independent unit of people that adhere to certain symbolisms, values, and beliefs while producing, consuming, and reproducing (Krishnaraj 1989). It is the household where the larger cultural norms and ideologies are interpreted and carried out. Clearly, however, household members may not be buffered equally due to age, gender, and resiliency, among other reasons (Das Gupta 1987; Engle 1996; Galvin 1995; Graham 1987; Miller 1997). Regardless of definition or discipline, anthropologists, psychologists, and evolutionary biologists recognize that childhood is a vulnerable period in which parental and child interests may not coincide, and a primary point in which natural selection takes places as rates of childhood death attest to. This research draws on several related fields to explore the interactive effects of social change and health as the socioecological niche changes with the presence of a new sibling (Figure 1.2). Since pregnancy often determines age at weaning and birth intervals of five years are rare with children under age five being most susceptible to disease and death, anthropologists are in an excellent position to examine associations among changing social roles, the socioecological niche, and health outcomes while considering evolutionary theory. Individual, household, and more global level forces both create and buffer stress by which interacting, overlapping, and competing processes thereby mediate health status. This examination of the negation process is fundamental for understanding the allocation of time and energy over the life course. This investigation complements large- scale cross-sectional research by focusing on the fine-grained description of one life event in the process of childhood – the transition from the youngest child to the older sibling; or in motherhood – addition of another child to the household or the household birth transition. The goal is to investigate the biological and social repercussions associated with weaning and the addition of a new sibling. This research draws on
17 medical anthropology, human population biology and life history theory to focus on reproduction as a source of social change that may be related to health outcomes of a mother, her youngest weaned child, and fetus/newborn.
18 CHAPTER 2
THE STUDY POPULATION
2.1 Introduction to the Area
The Manyara and Arusha regions of north-central Tanzania geographically represent one of the most culturally diverse areas in Africa (Figure 2.1). Topics covered in this chapter include information on basic history, climate and environment, health, social organization, motherhood, and child-rearing among the Iraqw speaking peoples living in this part of rural northern Tanzania. The cultural diversity in this small region of East Africa provides an excellent opportunity to carry out similar research among other linguistic groups living in the same basic ecological zone.
19
Figure 2.1. Distribution of languages in Tanzania and study area (Map from SIL International, http://www.ethnologue.com)
This research took place in the Mbulu District of the Arusha region from September of 2001 through November of 2002. During the course of the fieldwork, the Arusha Region was divided into two smaller regions: Manyara and Arusha. Haydom, the major town and center point in the research catchment, is located in the newly formed Manyara Region (Figure 2.2).
20
Arusha
Manyara
Figure 2.2. Regions of Tanzania and the splitting of the Arusha and Manyara Regions.
The first language of a vast majority of Tanzanians is of Bantu origin (Knappert 1987). There are two official languages in Tanzania: English and Swahili. Primary education is taught in Swahili and post-primary education is taught in English. The Mbulu District of Tanzania is unique in that it is the only place in Africa where representatives of each of the four main African language groups live in close proximity to one another (Ihanzu, Iramba, Hadza, Sandawe, Iraqw, Gorowa, Burungi, Mbugu, and Datoga) (Greenberg 1955). Those language phyla are Bantu (Niger-Kordofanian/Niger- Congo), Khoisan, Cushitic (Afro-Asiatic), and Nilotic (Nilo-Saharan) (Ehret and Posnansky 1982) (Figure 2.1). 2.2 An Abbreviated History The material remains for understanding human evolution are rich in Tanzania and date back to at least 4 million years ago (Burney 1996; Johanson and Edey 1981). Overall, little is known about the prehistory of the interior part of the country (Ambrose 21 1982; Murdock 1959; Winter 1968). Contact with various groups has been going on for centuries throughout the Indian Ocean with trading dating to at least the 8th century. Initial European contact, by Vasco da Gama, occurred in 1498; and was followed by 200 years of Portuguese colonization (1498 – 1698) (Winter 1967). In next two hundred years, coastal Tanganyika (mainland Tanzania) and its associated islands had ongoing relations with Omani leaders with Seyyid Said moving the capital to Zanzibar in 1840 (Moffett 1958). By 1881, the Germans held territory in East Africa and colonized Tanzania for 30 years. After World War I, the League of Nations turned this region over to Britain who ruled the country for another 40 years. The area was under a British protection beginning in 1918 through to independence in 1961. In 1964, Tanganyika (mainland Tanzania) and Zanzibar (formerly Unguja and Pemba islands) united to become the independent United Republic of Tanzania. Until the turn of the 20th century, most Tanzanians were peasants relying on subsistence agriculture (in addition to a small hunter-gatherer and pastoral populations). Since then, there has been a growing urban population, increased external trade, and increased planting of cash crops such as cotton, coffee, sisal, pyrethrum, cashew nut, tea, and tobacco (Lugalla 1995). The Germans nearly eliminated the coastal trading economy to focus on European needs like cotton and sisal (Iliffe 1971). With British colonization, the pattern remained the same but with more emphasis on coffee production (Raikes 1975). There is a minor market for cocoa, peas, castor, groundnuts and sunflower. The national market relies heavily on maize, sorghums, millets, rice, wheat, cassava, bananas, and fruits and vegetables (Hamersley 1972). 2.3 Population Growth Today, the parliamentarian system of governance has its capital in central Tanzania in the city of Dodoma; but coastal Dar es Salaam remains the commercial and economic capital of the country. The 2002 national census estimates 34.5 million people live in Tanzania (The United Republic of Tanzania, www.tanzania.go.tz), an increase of 22 million people since the 1967 census. The average growth rate for the nation is listed at 2.9% (2.8% in 1988). Population growth, however, varies greatly by region. For 22 example, the average growth rate in Lindi is 1.4% yet in the Kigoma region it is 4.8%. The Arusha region is on the high end of the continuum and up from 3.8% in 1988 to 4.0% in 2002. The growth rate for the newly formed Manyara region, which is where this project took place, is at 3.8% (Figure 2.3).
Figure 2.3. Growth rates reported from the 2002 National Census, Tanzania.
Like nested sieves, administratively, Tanzania is broken down into smaller and smaller units, with the village (kijiji) as the smallest official unit. There are 26 regions (mkoa), which are divided into districts (wilaya). Districts are divided into divisions (tarafa), which are further subdivided into wards (kata). Villages (vijiji) make up the wards and also may be broken down into smaller, but unofficial units called the subvillage (kitongoji) and then smallest unit is the ten-cell (ubalozi), which is made up of 10 households (range 5 – 20) and led by the nominated leader (balozi).
23 2.4 Physical Features and Environment Tanzania is located between longitudes 29 - 40° East, and just below the equator between latitudes 1 - 12° South. Tanzania is approximately 945,000 square kilometers (378,000 sq. miles) with over 59,000 square kilometers of lakes. It is the largest country in East Africa, and climatic variation characterizes the country. There is great variation in temperature, altitude, rainfall, drainage systems, soil types and vegetation across the country; it is marked by tropical, temperate, and arid climates. Average temperatures for the country range from 18° - 32°C; January is usually the warmest month with July being the coolest; of course, this is closely associated with altitude which ranges from sea level to the summit of Mount Kilimanjaro, the tallest mountain in Africa, at 5,800 meters (Figure 2.4).
Figure 2.4. Elevation map of Tanzania showing some natural features. 24 Geologically the country is divided into five regions. The Coastal Plains, which average about 160 km wide, lead into the Eastern Plateau. The Great Rift Valley is the third region and much of it has been filled in as a result of past volcanic activity. The fourth region is the Central Plateau which drains north into Lake Victoria and south to the Malagarasi River and ultimately Lake Tanganyika. The fifth region is the Western Rift Valley with its deepest point being Lake Tanganyika (Knappert 1987, Morgan 1972). To generalize, these five geological regions are marked by three climatic zones closely allied with altitude. The coastal plains, below 750 meters, are typically defined by tropical plants due to higher amounts of moisture and warmer temperatures. The semi-tropical zone, between 750 and 1,400 meters, includes the central and western plateaus; it is usually drier and cooler. In the dry season (June – September), temperatures may drop to 10°C at night. At altitudes above 1400 meters, or the “hill country”, people mostly live at ranges between 1,500-2000 meters. Annual and daily fluctuations in rainfall are variable by geography and altitude. Currently, the factor with greatest economic significance is rainfall. Settled agriculture is problematic in many parts of Tanzania because areas may not get enough rain year to year; in other words, the usefulness of rain is determined by its distribution in any given year which is notoriously unpredictable (Kenworthy 1964). It is rare for any area to have less than 250 mm of rain, most areas average more than 550 mm; however, if the rainfall is on the lower end of this scale it will lead to crop failure (Hamersley 1972). The Haydom area, where this project took place, often experiences localized famine due to crop failure because of a shortage of rain or unpredictable timing of the rains. 2.5 Introduction to the Iraqw 2.5.1 A Brief History: The Iraqw are one population of Southern-Cushitic speakers occupying several districts of these regions, primarily in the Karatu, Mbulu, Babati, and Hanang districts although they continue to expand into other areas (Figure 2.5).
25
Figure 2.5. Former Arusha Region with Babati, Hanang, Karatu, and Mbulu districts labeled.
The Southern Cushitic speaking peoples are thought to be the first food producers in East Africa (Ambrose 1982). Their estimated arrival to Kenya and Tanzania from southern Ethiopia is 3,000 – 5000 years ago (Ehret 1974; Kieran 1972). Prior to 1900, Iraqw speaking peoples lived in a very a small highland enclave in the Mbulu district referred to as Iraqw Da/aw (Lawi 1992, 1999; Snyder 1993; Yoneyama 1969; 1970). They were limited to this area because of the threat of cattle raids by the Maasai to the north and because of insect infestations to the south. With German and British control of Tanganyika, the Iraqw were protected from raiding parties, especially from the Maasai to 26 the north. The Iraqw mostly had good relations with their Datoga neighbors to the south. The Iraqw took advantage of amicable relations with the Datoga, sometimes referred to as the Barabaig, to begin to expand geographically out from the Mbulu highlands, or their homeland, in the early 1900s (Lawi 1992). Historian, Y.Q. Lawi states that the Iraqw, although open to intermarriage, cultural exchange, and economic interaction with other ethnic groups, remained relatively unchanged until the 1920s (1999). He believes that changes became evident by 1920 due to the large-scale influences of the colonial powers and missionaries (Lawi 1993; Winter 1967); and writes that the most marked changes occurred in the 1940s/1950s especially at the time when imported ideas about maize agriculture dominated. Since then, maize has become the preferred stable for the Iraqw and throughout much of East Africa (Lawi 1999) although the history of its adoption was marked with “tense resistance” (Lugalla 1995:5). By far, the Iraqw now comprise the largest proportion of the population in four districts of the Arusha region shown above in figure 2.8 (Snyder 2001). 2.5.2 Political and Economic Change: Additionally, movement out of the homeland area to different climatic areas led to a diversification of modes of production. Although the Iraqw always kept cattle and were perhaps the major supplier of cattle on the national market in colonial times (Kitching 1922 in Raikes 1975; Winter 1967), with migration, many Iraqw become herdsman and accessed the grazing lands of the Datoga to the south. Some Iraqw moved completely into a pastoral sector whereas others disregarded traditional modes of agricultural and developed less labor-intensive methods as they had access to larger plots of land in flatter areas (Iliffe 1979; Raikes 1975). Iraqw migration was not met with hostility to the south because there were few Datoga in this area and relations were friendly (Wada 1969). At this time, a northern expansion meant that the Iraqw entered Maasai grazing lands. Protection by the colonial government and several development schemes gave the Iraqw an advantage because the colonials viewed them as “suitably intelligent” as compared to the “violent” Nilotic populations and the “less intelligent” Bantu populations (Fosbrooks, n.d., in Raikes 1975; Meek 1953; Snyder 1993; Wada 1969).
27 Part of the reason that the Iraqw began to occupy new territory was because of their ultimogeniture type of inheritance and increasing population size (Snyder 1993; Wada 1969). Only the youngest male would inherit the land and home of his parents. The older sons would have to relocate and did not surpass the opportunity to move into new territories under the protection of the colonial government in the early 1900s. 2.5.3 Physical Environment: Haydom is a town that is at the center of this research catchment area. Haydom (also spelled Haidom), is situated on a highland plateau to the south and west of the homeland area near Mbulu town. The study area lies at an elevation ranging from 1650 – 1850 meters (5500 – 6050 feet). The eastern backdrop to this study area is Tanzania’s 4th tallest mountain, an extinct volcano, Mt. Hanang (3480 m) and to the west is a branch of the Rift Valley that forms the Yaeda valley (1300 m) (Figure 2.6) (Knappert 1987).
28
29
Figure 2.6. View of Mt. Hanang (left) and the Rift Wall (right) (pictures by M. Niemi)
29 The generalized rain pattern in the Haydom area is bimodal, or coming in two rainy seasons. The short rains (vuli) usually occur in November and December and the long rains (masika) take place between March and May; however the start of the rains is variable and may begin as early as January or February or as late as March/April. Rarely, if at all, does it rain in the cool, dry (and dusty) season between June and October. Temperatures usually range between 20° C and 30° C; it is a temperate climate with and averages of 750 mm of rain which usually ranges between 500 – 1000 mm by specific location (Olsen 2002). 2.6 Health 2.6.1 Brief History of Medical Care: Haydom is now a town center that has grown as a result of the opening of a Norwegian Lutheran Mission Hospital in 1953 (Haydom Lutheran Hospital, www.haydom.no) (Figures 2.7).
Figure 2.7. Medical Director, Dr. O.H. Evjen Olsen, of Haydom Lutheran Hospital (picture by Dr. Olsen).
The British Protectorate government requested placement of this hospital in the southern highlands of the Mbulu District. It is located approximately 300 km southwest of Arusha and 150 km south of Ngorongoro Crater between Lakes Eyasi and Manyara. The British expected the hospital to be most accessible to several geographically
30 marginalized populations including the Datoga, Hadza and Iraqw. At the time of its building, the immediate area was sparsely populated and it is recorded that only one Datoga family lived in the vicinity of the hospital at its building (Olsen 2002). The reason for this was the threat of trypanosomiasis, or African sleeping sickness, a blood- born protozoan infection that comes from one of two species – Trypanosoma brucei gambiense or Trypanosoma brucei rhodesiense and is transmitted by the tetse fly (Winter 1967). To alleviate the problem, the government cleared the bush in this area to destroy the vector’s habitat; the area became habitable by both humans and cattle. 2.6.2 Health Concerns: Although sleeping sickness is no longer a problem in this area, an increasing worry is the threat of HIV/AIDS. In the early 1990s, the prevalence of HIV sero-positives among those attending Haydom Lutheran Hospital antenatal clinics in the region was less than 1% (Hinderaker et. al. 2001). But studies in the late 1990s and in 2001 show that blood donor sero-positives ranged from 1.6 – 7.5% (HLH 1997, 1998, 1999, 2000, 2001, 2002a). A comparison of hospital admissions between 2001 and 2002 shows there was an increase in both AIDS, from 50 to 87 respectively and HIV patients, from 29 to 51 respectively (HLH 2003). Currently, there is an active HIV/AIDS prevention program under way in the area (HLH 2002b). The disease causing the most number of deaths in the area today is malaria (Olsen 2002; HLH 2003) (Figure 2.8). There are seasonal peaks and annual variation in malaria cases. The area is described as hypo to meso-endemic in transmission which means that it is subject to sudden increase in vectorial capacity caused by heavy rains, warmer and more humid weather, extended seasons due to these factors, and/or invasion of a more efficient vector. In other words, although endemic to the area, populations are prone to malarial epidemics.
31
Figure 2.8. Distribution of stable malaria transmission, Tanzania, East Africa.
32 Malaria is problematic for most Tanzanians, but among reproductive age women anemia is also a risk for poor reproductive outcome. Malaria is often associated with an anemic state and pregnant women are prone to iron deficiency (IOM 1990). Following the WHO’s definition of anemia, Hinderaker et al. (2001) report that 23% of pregnant women that attended Haydom Lutheran Hospital antenatal clinics suffer from anemia and have hemoglobin concentrations below the 11.0g/dl cut-off (WHO 1996). They also report that the risk of anemia changes by season, increasing by 6 times as much in the rainy season (March to May), and nearly doubling among those with malaria. A household survey (n = 2043) was conducted in the mid-1990s by Olsen et al. (2000). They estimate that households in the Haydom area have a total fertility rate of 7.40 (2000: 1294). In comparison to the Demographic Health Survey, this figure is higher than national figures reported in 1996 and 1999 (Tanzania Bureau of Statistics 1996, 2000). Olsen et al.’s work estimates risk of maternal death at 362/100,000. A second survey conducted at antenatal clinics estimated risk to be at 444/100,000 (or lifetime risk of dying due to motherhood is 1 in 38 and 1 in 31, based on these two surveys) (Olsen et al. 2000). They point out that these figures are lower than those in other comparable reports from Africa. Maternal mortality rates and are estimated to be between 316 – 1549/100,000 from reports they cite (Cutts et al. 1996; Le Bacq and Rietsema 1997; Olsen 2000; Oosterhusi 1993). Hemorrhage is the main cause of direct obstetric death in this region of northern Tanzania, and cerebral malaria is an underlying cause of maternal death (44%). Their study is the first to report this find which the authors argue needs further investigation (Olsen et al. 2000; Olsen 2002). A slight majority of women (55.5%) in the vicinity of Haydom Hospital deliver at the hospital; however women from the major tourist town of Arusha and from all over the region attend this hospital because of its excellent reputation and minimized costs of delivery (approximately 4.00 USD for normal vaginal delivery and 40 USD for a cesarean section). In 2002, a total of 3,533 births were recorded by the hospital; of these, 3368 were in-hospital deliveries, 27 were born just before arrival to the hospital, and 13 were attended to in homes (HLH 2003). Another 2,836 home births were reported to the hospital. Eighty-two per cent (2803) of the hospital deliveries were considered normal
33 singleton vaginal deliveries and 18% (605) were listed as abnormal (e.g., required operation, vacuum extraction, twin deliveries, or other complications), and less than 1% (5) were recorded as spontaneous abortions (<28 weeks) (HLH 2003). Sex of the newborn was recorded for 3,533 births, there were 1,825 (52.3%) males and 1,708 (48.7%) females born between January 1 and December 31, 2002; a ratio of 1.07 (males: females) (Figure 2.9).
Live Births Recorded by HLH in 2002 Sex
2000 1800 1825 1600 1708 1400 1200 1000 800 600 400 200 0 Total Number Recorded by HLH Male Female
Figure 2.9. Live births at Haydom Hospital in 2002 by sex.
Of the 3,533 recorded birth weights, 325 (10.5%) weighed less than 2,500 g; this is less than the national average which is 14% (UNDP 1999). A weight of less than 2,500 gram puts these children in a higher risk category for morbidity and mortality (Kramer 1987). The hospital perinatal mortality rate (PMR), due to complicated referrals, is not necessarily representative of the population as a whole. The average PMR for 2001 and 2002 is 55.8 per 1000 live births. Early neonatal mortality is estimated to be at 23.6 per 1000 live births (HLH 2001, 2002). Children under the age of five are at greatest risk for morbidity and mortality worldwide (UNICEF 2001). In 2001, the Haydom Hospital recorded 302 under five deaths (167 male and 138 female). In 2002, there were 270 under five deaths (130 male 34 and 140 female). In 2002, pneumonia, prematurity, malaria, birth asphyxia, and meningitis were the top five reasons for death. These causes are not much different from known caused as reported by the World Health Organization in 1999 (UNICEF 2001): perinatal condition, respiratory disease, diarrhea, vaccine-preventable disease, and malaria (Table 2.1). The top five causes of admission to HLH differ slightly with pneumonia, malaria, gastroenteritis, and anemia, prematurity as the top five reasons to admit (HLH 2003).
2001 Number of <5 deaths 1 Malaria 91 2 Pneumonia 65 3 Prematurity 43 4 Septicemia 25 5 Meningitis 12 TOTAL 236 2002 Number of <5 deaths 1 Pneumonia 55 2 Prematurity 41 3 Malaria 40 4 Birth asphyxia 23 5 Meningitis 16 TOTAL 175
Table 2.1. Causes of death for children under age five attending HLH in 2001 and 2002.
2.7 Culture and Ideology:
The origin of the word haidom/haydom is from the Datoga language; the area was primarily Datoga territory until the early 20th century. The word translates as a zebu cow’s hump in the Datoga language.
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Figure 2.10. The shape of the hill in the background is similar to that of a zebu cow’s hump (picture by M. Niemi)
The town of Haydom was named after this shape because of the obvious resemblance of the hill in the background to the cow’s back (Figure 2.10). As the Iraqw and Bantu populations migrated toward Haydom Hospital, the Datoga have become a minority on lands that once were once identified as their own.
Regardless of ethnic affiliation, the majority of the population in this area are subsistence agriculturalists, however a small but growing percentage are almost entirely dependent on money as a medium of exchange as they are employees of the hospital or have businesses in association with the town (i.e., own a shop/restaurant/hotel, work in a shop/restaurant/hotel, sell vegetables/fruit at the market) (Figures 2.11 and 2.12).
36
Figure 2.11. Typical shop in Haydom (picture by M. Niemi).
Figure 2.12. The Haydom market where potatoes, tomatoes, leafy greens and sunflower oil are regularly available with other items available seasonally (picture by M. Niemi).
37 The Iraqw, who are now the largest population living in the Haydom area, were historically described as agro-pastoralists because most people were subsistence agriculturalists. In the past, small grains like millet and sorghum were preferred. Now most Iraqw cultivate maize, beans, millet, and sorghum and, if possible, practice animal husbandry, primarily raising cattle but also goats and sheep, and more recently pigs (Fukui 1969). The homeland was not particularly conducive to large herds of cattle, but nearly every household had some cattle (Lawi 1999). As a result of geographic expansion, Christianity, and globalization, lifestyles do not necessarily coincide with pre- colonial ideology (Snyder 1997). A review of Iraqw cosmology provides information about the structure of belief systems which will be important for understanding discussions of ideology change since the time of migrations from the homeland of Iraqw Da/aw began in the early 1900s. These notions of change may in fact alter reproductive ideology which could negative consequences for reproductive age women. In the past, Iraqw mythology and belief systems were directly related to an individual’s mobility and land use, because of strong taboos linked to the male spirits associated with water sources and living below the earth, or the neetlaamee (neetlaang’w, sing.) (Lawi 1999; Snyder 1993). Being prone to anger, especially when taboos are broken, makes people vulnerable to the backlash of these community-specific spirits. Neetlaamee are said to act and feel in similar ways as humans. They are especially reactive to acts against moral code and have an aptitude for negative feelings like jealousy and rage (Snyder 1993). Quarantine (meeta), is used to protect individuals, their families, and community from the anger of the neetlaamee which may react, for example, by withholding the rains (Lawi 1999; Snyder 1993; Winter 1966). Many quarantine rituals result from exposure to death or body fluids (like miscarriage or breastfeeding). Individuals in quarantine are potentially polluting to others; therefore seclusion is essential until ritual appeasement is satisfactory to the spirits or until a time-specific ritual cleansing has occurred. Reproductive age women are especially vulnerable to acts of the neetlaamee. For example, before expansion out of the homeland, women rarely left their community even to do farm work or to collect firewood for fear of angering the spirits which may take
38 revenge on the woman, her family, and the entire aya, or neighborhood. Reproductive age women would stay away from water sources to avoid angering neetlaamee and avoid risk of revenge. People primarily interacted with those living in close proximity to them rather than traveling far distances (Thornton 1980). In other words, the network of neighbors was connected spiritually and geographically and arguably the community (aya) was the most important social grouping besides the household (Lawi 1999; Snyder 1993, Thornton 1980). Importantly, neighbors were not always relatives. A second equally important component of cosmology is the female creator who acts quite differently in comparison to the male neetlaamee. Looaa, who is more remote from every day life, does not need appeasement and never expects sacrifices of animals (Snyder 1993). Looaa and neetlaamee are complementary ideas in the minds of Iraqw and mirror expectations of aspects of gender roles in general (Snyder 1993; 1999). Women are like Looaa because they are expected to be gentle and generous; therefore, feedback about a woman’s role as mother is not expected. The same applies to the female deity; she does not require sacrifice or praise. For a woman, her status in society comes from her success as a mother; being a mother makes a woman morally superior to all others in the society (Snyder 1993). Mothers are said to provide the blood for all Iraqw whereas men’s contribution is mainly the bones. Although the Iraqw are patrilineal, uterine kin remain important and central to aspects of social relations. In other words, women are not necessarily less valued in Iraqw society by virtue of their gender; Iraqw men and women each have contributions to society and act in a complementary fashion to one another (Snyder n.d.). Harmony is a central tenet in Iraqw thinking (Snyder 1993), so ideally, work is done in a peaceful manner which would positively interact with fertility of the land, animals and people. Iraqw lifeways, as described by the elders (and researchers), highlight community consensus, and emphasize that all must agree to do what is best for the community at large to keep peace (Lawi 1995). As a gerontocracy, elder men meet and work toward consensus by listening to the opinions of all, including women’s opinions about the community. After each man has his say, the group will come to a consensus to address and resolve some problem. They
39 would say “‘being of one heart’ is crucial to community survival” (Snyder 2001:129). However with rapid changes associated with the national government, international economies, and Christianity, life for younger Iraqw is different from that described by elders. Tanzanians and the Iraqw are members of a national government that was post- colonially socialist (Ponte 2002; Snyder 2001; Yeager 1989). In 1992, Tanzania became a multi-party democracy and held their first elections in 1995 (Snyder 2001). With such changes, Tanzanians, in general, increasingly depend on money as a medium of exchange and the Iraqw although somewhat geographically isolated are also becoming more and more integrated into a market economy (Mous 1992; Ponte 2002; Rekdal 1999). A rapidly changing economic system, among this high fertility population (TFR = 7.4), is particularly important as it has changed the rules governing social relationships and gender ideology (Olsen 2002; Snyder 1999; Sen 1999). Historically, reproductive and productive roles of men and women were complementary; with women in the domestic sphere and men moving in and out of the public sphere; but all for the good of the community (Snyder 1999). The increased footing of Christianity through missionary work, mandatory schooling, and introduction of the market economy at the turn of the 20th century contributed to the changing gender roles of men and women with each generation (Rekdal 1996). Colonial policies were, of course, based on gender ideologies of Europeans. Many of the schemes and policies of development were aimed at the colonizer’s idea of gender roles; therefore, status and authority of Tanzanian men, although below the colonials, was automatically above that of women. Over time, with education, greater access to the market economy, and government positions, men became fragmented as well and leaving a segment of them equally as marginalized as women (Snyder, n.d.). Arguably the most profound change is in social ideology; there is much less commitment to the community: Modern resources, as privately owned assets, advance the idea of separateness of individuals. The introduction of resources oriented toward cash markets creates an individualizing pattern of exchange, making it possible for people to engage more with market and invest less in their social relationships (Snyder 2002: 170). 40 Different notions of community have recently been formed through interaction with churches (missionaries), government, and markets (Snyder 2001, 2002; Rekdal 1996). Iraqw growth and total fertility rates indicate that the Iraqw-speaking population is growing at higher rates than the national average. However, there is a negative side to this growth and expansion as well; most of which relates to identity. Community, age specific, gender, and economic roles are changing as compared to former descriptions by elders, anthropologists, and historians (Lawi 1999; Rekdal 1999; Snyder 1993). Iraqw identity is being redefined on many fronts such that “there is no uniformity of opinion or response to the rapidly changing political and economic events taking place” (Snyder 2001: 145). Among younger Iraqw there is a noticeable decline in attention to social control mechanisms. Snyder identifies inter-generational conflicts in her work on elders’ authority. “Today, elders are increasingly marginalized from politics and material production as the state has taken over may of the functions (such as allocating land and settling disputes) which were previously theirs” (Snyder 1997: 563). Her work illustrates that roles associated with age, gender, and community position are in a state of change. She points out that although many traditions and rituals remain the same, the authority associated with such rituals has been eroded as younger generations have grown up in different political-economic contexts. Her work is evidence that economic shifts affect Iraqw identity and threaten aspects of former Iraqw ideologies. For example, one of the elders’ complaints is that the younger Christianized Iraqw will not volunteer animals for rituals and may even demand monetary compensation for these animals (Snyder 1997). Therefore, even the elders’ authority in the ritual sphere is being eroded. This is entirely against the Iraqw moral ideology which is more familiar to the elders in the community as younger members of families are influenced by ideas of modernization (maendeleo) (Snyder 1996; 1997; 2001, 2002). Generally, Iraqw women’s authority is defined by motherhood (Snyder 1999). In the discussion that follows I focus on the impact that growing up in different political, social, economic and ideological contexts has had on women, especially on their workloads and relationships. These changes, in turn, affect their options for household
41 provisioning. In the past, a woman’s range of activities was partially limited by rules associated with cosmology because it placed limits on her mobility. But as a result of relaxed pollution beliefs and greater demands for money, women’s mobility and workloads are changing to reflect larger socio-economic standards concerning religion, western education, and the capitalist market economy (Lawi 1995; Rekdal 1996; Snyder 1999). For many women, maternal responsibility now includes activities to generate some income to pay for education, medical bills, and taxes. However, because of women’s political protests, the head tax on females has recently been revoked because “to find ways to raise the money necessary to pay the tax, the entire household would suffer” the consequences (Snyder 1999: 249; Blystad 1999). In some cases, men are seeking economic gains away from home, which, in turn, increases women’s workloads because they are left to care for the family, farm, and herds. Women have also begun income generating activities such as beer brewing and the selling of vegetables, charcoal, milk, eggs, and chickens in order to meet many of these household needs. As in the past, the intricacies of household survival are primarily the responsibility of the woman (Snyder 1993). Although, “not passive victims of external modern forces” (Rekdal 1996), the recent emphasis on the nuclear family, western education, private assets, and disintegration of community obligation, in addition to colonially imposed notions of gender ideology makes women’s daily negotiations inconsistent especially concerning dependency on social relations (Lawi 1995; Snyder 2002). This modern identity leaves many men quite marginalized from the economic sector and many are at a loss as how to provide household needs; crop failure is more common and many cattle have died of disease. Alcoholism has been on the increase in recent years which likely reflects men’s inability to access the monetary sector and maintain their responsibilities to the home. Men admit to being dependent on women to know what the household may need, but limited access to education, economics, and exclusion from national politics exacerbates the problem (Snyder n.d.). As expectations of men’s’ and women’s’ roles are changing, one aspect remains the same for women – their responsibility in maintaining the particulars of household. However, their status and
42 authority as mothers has actually declined since the colonial experience (Snyder n.d.) Women are expected to identify and provide most of the basic needs of the household members which includes cleaning, food provisioning, clothing, school supplies, and health needs. However, their increased workloads resulting from a decrease in men’s participation in heavy labor and herd maintenance can translate into negative effects for all household members and especially children since women remain even more marginalized than men (Snyder n.d). It is fairly unusual for children under the age of five to participate in household labor. However, children over five years of age are capable of watching small herds and it is quite normal for younger children to accompany them in this duty. Mandatory schooling has many older children in school for daylight hours. Children are supposed to begin school at age six or seven and will be in school from September to July for at least seven years of free primary education (not including uniforms and supplies). The intentions of the Tanzanian government are good in that primary education is compulsory; however, there are unintended consequences that affect women’s workloads and social relationships (2.13).
Figure 2.13. Primary school students in Haydom (Haydom Lutheran Hospital, www.haydom.no).
43
First, older children may not be at home for the majority of the day which leaves women without child helpers. There is more of a demand on women to provide money to their children for school uniforms and supplies and if they go on for higher education, expensive tuition fees. Since the 1970s enrollment rates have actually dropped to below 70% and gender gaps may be exacerbated if parents must decide who to educate because most will decide to educate males over females (Omari and Mbilinyi 2000). Intergenerational conflicts arise as well because informal education is lost to formal education as children are not active participants in the environment in which they would learn about social control mechanisms, norms, and morality of the Iraqw in general (Creighton and Omari 2000; Lawi 1995; Snyder 1993). Although no population is static, the Iraqw-speaking peoples are experiencing changes on many fronts – political, economic, and ideological. As Rekdal (1996) points out, the Iraqw are labeled as both traditional and progressive. As with most populations, people make the best of the situation; the Iraqw are no exception and work hard to maintain certain ideologies while at the same time participating in the “modern” economy. These changes have particularly affected Iraqw social systems. Indeed change is not without consequences and women and children tend to be the first to suffer at the expense of such change. The health of Iraqw women and children is the primary focus of this research and is studied in the context of the described history and current circumstances.
44 CHAPTER 3
METHODOLOGY
3.1 Introduction This chapter describes the various methods employed to conduct this research including anthropometry, survey, and time allocation. A presentation of the sample population and a basic chronology of the data collection process provide information to understand the strengths and limitations of these data. Ethnographic data, through participant observation, were collected to contextualize the biological (health and growth), nutritional, psychosocial, household, and socio-economic data. 3.2 History of the Project Although a major portion of this research was conducted between September 2001 and November of 2002, contacts with the Tanzanian health community and Haydom Lutheran Hospital (HLH) began in August of 2000. During the first phase of the project, I made in-country contacts at the University of Dar es Salaam and Muhimbili University College of Health Sciences and visited the field site in north-central Tanzania; Haydom is located in the Mbulu District. The medical director of HLH, Dr. Evjen Olsen, gave me permission to work in cooperation with the Maternal and Child Clinics and Maternity Ward at Haydom Lutheran Hospital. That August, I collected basic health information and reports from the hospital staff. The second phase of the project began in September 2001. During the last week of September 2001 until the early part of October, I stayed in the economic capital, Dar es Salaam, to finalize research clearance (Appendix A) and reestablish relationships with professors at the University of Dar es Salaam (Dr. Y.Q. Lawi, history and Dr. Tungaraza, medical anthropology) and Muhimbili University College of Health Sciences (Dr. Sylvia Kaaya, psychiatry) (see Appendix A). After receiving permission to conduct research in Tanzania at the national level, it was
45 necessary to get permission at each smaller unit of government. In October, I was granted permission by the regional commissioner of the Arusha region, the district officers of Mbulu and Hanang districts, as well as from village leaders located in the project area: Bisgeta (Bisiyan and Getarer), Getanyamba, Haydom, Harar, Maghang, Mewadan, and Ng’wandakw. All protocol was approved by the Institutional Review Board (IRB) at Ohio State University before submitted to the Tanzanian government for final approval (Appendix B) To begin research, it was necessary to establish my identity in the community. With the help of research assistants (one older bilingual mother from the local women’s group – Akina Mama (Iraqw and Swahili); and several trilingual female secondary school students (Iraqw, Swahili, and English), I introduced myself and the project to the smallest recognized units in each village, called the balozi, as well as to both religious leaders and local citizens. It was through these introductions that recruitment of volunteers fitting the sample criteria began. 3.3 Sample Selection and Criteria The researcher and assistants would walk through each balozi asking women about their pregnancy status; thus employing a snowball sampling technique in areas surrounding Haydom town. If the respondent affirmed pregnancy, then the researchers would explain the research project, read them the consent form and ask for participation. This sample is not random. In order to understand the development of younger families, fifty-seven women were located who initially met the following inclusion criteria.
1. The mother must be pregnant, preferably less than 7 months
2. Mother must experience a live birth (miscarriages and stillbirths were not included, n = 2)
3. Maternal age between 18 – 30 at the time of recruitment
4. Parity of between 1 and 3
5. Index child must under the age of five at the time of recruitment
6. The index child must continuously live in the mother’s household (e.g., if relocated during study were not included, n = 2) 46
7. The newborn must live until the final follow-up at six months post partum (neonatal deaths, n = 2)
8. A minimum of two measures were acceptable before birth, a minimum of five measures acceptable after birth (if earlier delivery than expected occurred then participants were excluded due to lack of measurements before birth, n = 5)
These eight requirements had to be met to remain in this project focusing on relationships among the triad throughout one birth transition (mother, index, and neonate). Eleven women who were initially recruited did not meet requirements 6, 7, and/or 8. 3.4 Data Collection The researcher and assistants would collect behavioral observation data in 4- or 8- hour blocks of daylight hours (between sunrise and sunset). The name of specific activities were recorded for each mother and index child (e.g., making fire, carrying child, collecting wood, walking to the neighbors, playing with other children). The time spent on each of these activities was recorded to the nearest minute. With each activity change, the researcher would record the distance in meters between the mother and index child to get an idea of the average amount of contact time there was between mother and index child and changes over the course of the birth transition. When the child was out of the mother’s sight distance was recorded as “not seen”. An effort was made to collect data on a “typical” day; therefore no observations were recorded on Sundays because most families spent the day at church and socializing rather than participating in everyday weekday activities. The activity data were divided into major categories including lying about, house cleaning, food preparation and service, washing clothes/dishes, eating, sleeping, child carrying, carrying other items (wood, water, etc.), breastfeeding, bathing oneself/child, playing, or farming activities for the analysis. These data were then calculated as a percentage of time spent in those activities. Activities in which the mother could not see the child were not included in these averages of proximate distance to mother. Time spent “not seen” was recorded separately as a percentage of time spent out of the mother’s sight in a given block of time. Observations about episodes of crying and comforting were also recorded to assess some aspect of behavioral interaction
47 between mother and index child. These data are compared for change and differences in the late stages of pregnancy through the early stages of the post partum, or over the course of the birth transition. Following the standards set in Lohman, Roche, and Martorell (1988), the mother, index child, and newborn were measured monthly over the course of the birth transition. Preferably, participants were measured three times before birth and six times post partum; however occasionally the mother and index child were measured only twice before delivery and less than 5 in the post partum. Each neonate, or newborn, was measured the first time within 24 hours of birth. Thereafter, the infant, or newborn sibling, was measured a maximum of 6 times. All measures were taken by the researcher until May of 2002 at which time, illness inhibited participation and one trained research assistant took over and recorded all measurements with the help of a second trained research assistant. The following measures were recorded monthly for triad: Maternal: Height (cm) Weight (kg) Body Fat (%) Circumferences (cm): mid upper arm (MUAC)and calf Skinfolds: upper arm, calf, subscapular, and supraumbilical (mm)
Index: Length (cm) Weight (kg) Circumferences (cm): head, mid upper arm (MUAC), and calf
Neonates (within first 24 hours): Length (cm) Weight (g) Circumferences: head, mid upper arm (MUAC), calf, and chest
Infant: Length (cm) Weight (g) Circumferences: head, mid upper arm (MUAC) and calf
All measures were taken on the right side of the body (with the exception of one mother who was measured on the left calf because of a snakebite injury to the right calf).
48 Skinfolds were measured three times to the nearest millimeter using a Lange Skinfold Caliper. An average of the three measures was recorded in the database. A fiberglass measuring tape was used to measure circumferences in centimeters to the nearest millimeter. A Tanita TBF-521 Body Fat Monitor/Scale was used to assess maternal body fat changes throughout the birth transition. The accuracy of these measures is limited because of the woman’s reproductive state (TANITA 1996). Pregnancy and lactation obscure measures because bioelectrical impedance analysis is calculated by measuring the resistance of a low frequency electrical current through the body. The flow through fat is slower and through muscle is faster (TANITA 1996). It is not the absolute values that were important but rather the relative values over the course of the birth transition that were used and compared to other body composition measures (e.g., skinfold measures). Weight scales were calibrated daily using five and ten-kilogram weights (adult and index: A & D UC-300 Precision Health Scale; infant: SECA chica 345). A 0.5 x 0.5 meter board was used to make a flat and level area for measuring. Women were asked to remove all extra clothing including shoes, usually leaving a kanga (rectangular cloth used as a skirt) or a skirt and shirt/sweater. Often women wore the same clothes for each measure; therefore differences due to clothing changes are minimal and are not subtracted from the total. Commonly the index child wore minimal amounts of clothing and the same outfit throughout the course of the fieldwork, thus clothing was not subtracted from the total for the index child either. If the index child acted uncooperatively, mothers (or occasionally fathers) would hold the index child and the parent’s weight would be subtracted from the total (Figure 3.1). To minimize movement, keep neonate/infants warm, and facilitate a quicker reading, neonate/infants were wrapped in a kanga (rectangular piece of cloth) to measure weight; the weight of the kanga was subtracted from the total weight by using the tare option before the measure occurred. To measure maternal height to the nearest millimeter a standard anthropometer was used. To measure the length of the children, a hand-made baby board was used, and for infants a Measurement Mat glued to a plexiglass platform was used; regardless of age, recumbent length was recorded because of ease of measure; however throughout the remainder of the dissertation length and height are used interchangeably
49 but recumbent length measuring should be assumed. Depending on the situation, the board was lying flat either on the ground or on a Table while one assistant would hold the child/infant’s head firmly against the raised edge of the board/mat and another assistant would straighten the legs and announce the measured length to the nearest millimeter. If measuring length was difficult, the child would be measured three times over the course of taking measures and the average measure is recorded in the database.
Figure 3.1. Father helping researcher to measure the index child.
It should be noted, that every triad was not measured in every month. The following table shows the number of triads measured; these n values should be assumed to be consistent throughout the document unless otherwise stated (Table 3.1).
50
Monthly N Measure -7 1 -6 5 -5 11 -4 24 -3 40 -2 46 -1 46 B* 38 1 46 2 45 3 44 4 44 5 44 6 42 7 20
Table 3.1. Number of triads measured in each month (B = birth of sibling; * note: most mothers were not measured immediately after birth).
In addition to anthropometric data, the interview and survey information was recorded to help define variation among the participant population:
1. Regional Data: recorded all hospital births by women residing in villages located in the project area over the last 5 years (1998 – 2002). Data include maternal age, parity, gravidity, complications, sex of child, birth weight, and outcome at time of release. Although not included in these analyses these data were collected from hospital records (not included in thesis; forthcoming).
2. Background Information: residence, birthplace, ethnicity through maternal and paternal clan (ukoo) membership, marital status, birth family size and status (mother, father, brothers, and sisters), education level of mother and husband.
3. Reproductive Histories: age, parity, gravidity, date, place and outcome of previous pregnancies/births, weaning status, and pregnancy sickness.
4. Household Composition: age of husband, birthdates and ages of all children, gender and age of other members living in the household, number of animals, size of landholdings and amount of land farmed.
51
5. Health data: monthly the types of illnesses, duration, severity and treatment of illnesses were recorded for each member of the triad by maternal recall.
Specific Interviews: Interviews and surveys were used to assess several components expected to define variation in the developmental niche (Appendix C): 1. Family environment (changes in household composition, animal counts, and familial interactions).
2. Maternal psychosocial well-being (recent emotional well-being, relationships, basic quality of social relationships).The Hopkins Symptom Checklist-25 was employed as a survey instrument to assess levels of emotional distress (see discussion below).
3. Maternal perception of child well-being and adjustment (how well is your child doing since the newborn arrived?)
4. Maternal social network (visitors, lists of important people). A 13 question social support survey was used and women were also asked to free list members of their social support network. An eleven question survey expected to assess autonomy was also used.
5. Pregnancy sickness and cultural ideology about pregnancy.
6. Post partum cultural ideology.
Approximately 6 – 8 hours of activity were recorded for each mother and index child monthly from December 2001through June 2002. One researcher would record the basic activities and interactions of the mother and index child and the distance between them as activities change. The following information was recorded to better understand the household and maternal and child relationships:
1. Counts of animals present that morning.
2. Number of visitors to the household.
3. Distance (m) to index child (for mothers), distance to mother/caretaker (for index).
52
4. Each major activity change was written down for both mothers and index children.
5. General emotional responses to changing situations recorded for index child.
Although basic dietary information was recorded during each visit, no direct measures of intake were recorded. Women were asked to recall food intake from the previous 24 hours; 248 reports of 24-hour intake were collected. Historically, Iraqw women had altered diets during pregnancy (e.g., they could not eat eggs); because of this knowledge, I interviewed women about changes in diet although no one in this sample changed their diet during pregnancy. Women said that egg restriction during pregnancy is no longer a common practice; many attributed the change to classes taught while waiting at antenatal clinics. A pregnancy sickness survey was conducted to assess whether symptoms experienced during pregnancy were associated with birth outcome. Women (n = 198) in the maternity ward voluntarily participated in the survey the day after they gave birth at Haydom Lutheran Hospital. Pregnancy sickness surveys were conducted and show that food preferences did influence diet breadth, but not necessarily nutritional status. Post partum diet is known to change as well; therefore information on post partum diet was recorded for each mother. For example, at least in the first month or two after birth women would not eat leafy greens because it was thought to cause the newborn to have diarrhea. The slaughtering of small herd animals (goat or sheep) is required to return a woman’s strength after birth. Other meats were also eaten including chicken and beef. Since weaning begins as soon as food other than breast milk is introduced to the newborn, women were asked about the introduction of liquid and solid foods into the newborn/infant’s diet. Preliminary steps were taken to create a culturally appropriate psychosocial stress questionnaire. A 25 question symptom survey, compiled from the Hopkins Symptom Checklist-25 (Wider 1948; Deogratis et al. 1973; 1974) was used to test for differences in mean anxiety/depression scores. There are 10 items assessing anxiety and 15 items assessing depression. The Hopkins Symptom Checklist-25 has been tested in Tanzania 53 (Appendix E); the HSCL-25 has been used in variety of settings and translated successfully into several languages including Swahili (Hinton et al. 1994; Kaaya 2002; Mollica 1987; McKelvey et al. 1997; Winokur et al. 1984). The 25 item test was independently translated and back translated by two local speakers who are fluent in English, Swahili and Iraqw languages. After translating the questions, age and gender-matched focus groups were conducted to discuss the meaning of these questions and decide whether or not to exclude some of the questions. The first difficulty was about sexual appetite (#14), the second referred to suicide (#20) and the third problem was about loneliness (#19). Based on advice from translators, and after discussing the questions in age-matched focus groups, it was decided that a more appropriate way to ask question #20 about suicide would be “have you thought about hanging (men)/poisoning (women) yourself?” rather than “have you had thoughts of taking your life?” The third question, # 19 was rewarded to say “do you feel that you cannot speak in front of others or that you have nothing important to say?” rather than simply asking if the woman felt lonely. Although initially considered culturally inappropriate, these questions were left in the survey after revision because there was variation in responses in pre-tests. Cronbach’s alpha was used to test for internal consistency and it is fine at .90. A functional social support survey and a survey concerning autonomy were used in conjunction with the HSCL-25. Internal consistency values for these surveys were much lower at .80 and .75, respectively. 3.5 Data Analysis The following variables were used to address the major research questions: 1. Will there be a change in anthropometric measures, especially in the rates of growth by the older sibling (index child) throughout the birth transition? A. Dependent variables: rate of growth change, birth outcome, z-scores compared to reference population (CDC 2000) B. Independent variables: time (BB – before, PP – post partum), child temperament, child adjustment level, maternal well being (physical status), time in direct contact with mother, dietary recall, morbidity, age at weaning, lactational status at conception and into pregnancy, birth space interval
54 C. Control variables: age, parity, gravidity, village, biodemographics
2. Are changes in body composition of the mother reflected in the newborn and/or index child throughout the birth transition? A. Dependent variables: growth, body composition, morbidity, birth outcome, z-scores compared to reference population B. Independent variables: time (BB/PP), social setting – context of household help, social network, maternal well being, diet breadth, nutritional buffering, socioemotional interactions C. Control variables: age, parity, gravidity, village, biodemographics
3. Is maternal well being and social status, assessed by her support network, psychosocial stress levels, autonomy, access to helpers, and household composition, associated with outcome variables for any of the three members of the triad (mother, index child, and newborn)? A. Dependent variables: 1. HSCL – 25 scores a. independent variables: age, parity, gravidity, biodemographics, village, residence setting (virilocal), household setting, household help, wealth, employment status, education, social support network, major worries 2. Social Support Network a. independent variables: free lists of dependable individuals, names of individuals, individuals on list seen in the last week, last two weeks, and last month, visitors/visits b. independent variables: helper present to do some household duties, depend on relatives if need help with work or childcare 3. Autonomy a. Independent variables: ability to sell and buy items; feelings that cared for by others, ability to visit others, relationship with husband and other family members; ability to care for children 4. Household/Wealth a. independent variables: cattle, building, plows/carts, land owned/farmed, type of housing, type of residence (virilocol, neolocal)
55 Data analysis was done using SYSTAT 10 (SPSS, Inc. 1996). Descriptive statistics including mean, median, and standard deviations were calculated. Mann- Whitney U test statistics were used to test differences between subgroups among the households because sub-sample sizes were not equal or may not be normally distributed. Then same is true for comparing means of more than two groups, most often the Kruskal-Wallis test statistic was used instead of the usual ANOVA/MANOVA. In order to understand relationships between household variables and dependent variables, correlations, linear regression and general linear models were employed. Codes for variables are listed in Appendix E and correlation coefficients for various groups of variables are listed in Appendix G. Using EpiInfo 2002, I was able to include height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) z-scores to use for monthly comparisons because these measures are based on age rather than distance between measures. All z-scores represent comparisons to the CDC 2000 reference population (Cameron 2002; Kuczmarkski et al. 2000). These charts are a revised version of the National Center for Health Statistics growth charts which came out of the National Health and Nutritional Examination Survey (NHANES) which has collected height and weight data on American populations for nearly 50 years (Cameron 2002; DeOnis et al. 1997; National Center for Health Statistics 1994). These reference values are a little more representative than earlier versions because measures from breastfed children are now included in the reference population.
56 CHAPTER 4
RESULTS I:
DESCRIPTIVE DEMOOGRAPHIC AND SOCIAL STATISTICS
4.1 Introduction This chapter presents descriptive statistics from household surveys as well as basic anthropometric data for the triad over the course of the birth transition. 4.2 Demographic and Social Composition 4.2.1. Household Sociodemographics: Women participating in the research project lived in one of seven villages* surrounding Haydom town center (Table 4.1).
Area N Percentage of Sample Bisiyan 7 15.2 Gangay* 4 8.7 Getanyamba 7 15.2 Harar 10 21.7 Maghang 1 2.2 Mji B* 11 23.9 Ng’wandakw 6 13.0 Total 46 99.9
Table 4.1. Distribution of sample by area surrounding Haydom Hospital (* indicates a division of the village of Haydom)..
The average household size was 5.3 individuals with a minimum of 3 members and a maximum household size of 10. Eight couples (17.8%) were living in the home of the father’s husband; thirty-seven couples (82. %) were not. Nearly half of the sample (48.8%) could easily walk to the in-laws home; whereas 52.2% could not walk there as 57 easily. Twelve couples had another person (usually a relative) living in their home (27.3%); thirty-two couples did not have anyone besides husband, wife and children living in the home with them (72.7%). Mothers tend to be less educated than their husbands on average (6.2 vs. 6.7 years, respectively). There were three men and three women who were not educated at all. The three men without education were each married to women with 4 years of education. The three women with no education were married to men with 7 years of primary education. Therefore, none of the uneducated men/women in this sample were married to a spouse who was also uneducated (Table 4.2).
58 Variable N Mean SD Total number of people in household 47 5.298 1.382 Husband age 38 30.237 5.925 Husband education 44 6.682 2.409 N No % Yes % Live in the same house as in-laws 45 37 82.2 8 17.8 Have household help 45 10 21.7 36 78.3 Index child can walk to in-laws alone 46 24 52.2 22 47.8 Husband’s mother is a helper 46 19 41.3 27 58.7 Someone other than immediate family members lives with couple 44 32 72.7 12 27.3 Live in virilocal residence, or in close proximity to husband’s relatives 46 20 43.5 26 56.5
Table 4.2. Household sociodemographic data. 59
59 4.2.2. Household Economics: 4.2.2.1 Husbands’ Employment Status: Each household in the sample grew at least some food for subsistence. Just over 40% of the households surveyed were subsistence farmers with no other means of employment (54.1%). Twenty men (43.5%) worked for an income and of those, two men worked as local government officials (balozi – ten-cell leaders). Seven men (15.2%) were considered jobless due to health problems, alcoholism, or dependency on others for food and income. In other words, they were not contributing consistently to household production. In sum, 41 men (84.8%) are working whereas seven men are not working at all toward household production (15.2%) (Table 4.3). All of the men living in Mji B (town center) do not work as farmers; eight out of 10 work for money and two are unemployed.
N % Fathers/Husbands Farm 19 41.3 Government 2 4.3 Labor 18 39.1 Unemployed 7 15.2 Mothers/Women Farm 23 50.0 Home 13 28.3 Brew Beer 3 6.5 Tailor 2 4.3 Market 2 4.3 Labor (kibarua) 3 6.5
Table 4.3. Employment status of father/husbands and mothers/women in sample
4.2.2.2 Women’s’ Employment Status: The women also had a variety of productive roles, although most were primarily farming in addition to maintaining the household; twenty- three (50%) women were categorized as primarily farmers. Thirteen (28.4%) women maintained the household and did not participate in farming activities or planted small gardens outside of the house, three women (6.5%), in addition to farming, regularly brewed beer for income (although another 4 women mentioned brewing beer on occasion 60 but not regularly). Three women (6.5%) worked for others to earn an income (kibarua); for example, they would help fix houses or farm for other people. Two women (4.3%) were tailors, and 2 (4.3%) sold fruit and vegetables at the market (Table 4.3). Maternal employment status is related to distance to town center. Eight out of eleven women in Harar (far from town center) were farmers. In Mji B (town center), six out of 10 were housewives and four out ten worked for others for money. In Getanyamba (far from town center), six out of 9 women were farmers, one was a tailor, and 2 worked for money. The general trend is that women living nearer to town center are not farmers. This is reflected in living arrangements as well. In Harar and Getanyamba, the majority live in virilocal residences (10/11 and 8/9, respectively). In Mji B, two out of ten live in virilocal residences. 4.2.2.3 Animal Husbandry: Twenty-two households (52.2%), a slight minority, owned cattle. Twenty-four households (47.8%) were without cattle. The average number of cattle owned was 3.3; however, the median is only 1.5 cattle (Table 4.4). Four households (8.7%) owning cattle had some away on loan to other family members; seven households (15.9%) had goats away on loan, 2 (4.3%) had sheep away on loan and 1 household (2.1%) had a donkey away on loan. (Table 4.5) No one sampled had pigs on loan because pigs are a fairly new introduction and are usually only raised to sell on the market.
Animal Owned N Mean SD Cows 46 3.283 4.806 Goats 46 3.543 5.269 Sheep 46 2.543 5.124 Donkeys 46 0.130 0.542 Pigs 46 0.326 1.248
Table 4.4. Average number of animals present owned.
61
Presence (n = 44) On Loan (n =46) Yes No Yes No N % N % N % N % Cattle 22 52.17 24 52.174 8.69 42 91.3 Goats 26 56.52 20 43.487 15.9 35 76.1 Sheep 16 34.78 20 43.482 4.34 44 95.66 Donkey 43 93.48 3 6.52 1 2.17 45 97.83 Pig 42 91.30 4 8.70 0 0 0 0
Table 4.5. Animals on loan.
4.2.2.4 Wealth Status: Wealth status is assigned based on the type of housing and the presence of plows and carts. The housing types can be distinguished by floor and roof variations. The following categories are used to describe housing. A category of “1” represents housing with mud walls and thatched roof, a category “2” is mud walls with a flat top roof, a category of “3” is mud walls with a tin roof, and a category “4” is brick walls with either cement floors and/or a tin roof (Table 4.6) (see Figures 4.1). It is assumed that the costs of cement and tin reflect on wealth status although these are certainly not the only measures of wealth.
Housing Type N % 1 Mud walls, thatch roof 30 66.7 2 Mud walls, flat roof 3 6.7 3 Mud walls, tin roof 5 11.1 4 Brick walls, tin roof 7 15.6
Table 4.6. Number and percentage of triads living in each category of housing.
Households are categorized into 3 major wealth categories (Table 4.6). A category of “0” is relatively poorer than compared to the average household. Most of these homes are of housing types 1 or 2. A wealth category of “1” is average. These are homes of any type that may have a plow or household items like tables and chairs present. A wealth category of “3” means that the house has cement floors and/or a tin 62 roof and that a plow and/or cart may be present in addition to furniture which is quite costly (Table 4.7).
Wealth Category Rank n = 46 % Very poor 0 6 13.0 Average 1 22 47.8 Above average 2 18 39.1
Table 4.7. Crude wealth categories.
63
64
Figure 4.1 Variation in types of housing.
64 Wealth may also be associated with the total number of buildings present on the participant’s plot of land. There are six women in the lowest wealth category; five out of six of these women (83%) have only one building; one out of the six has two buildings on the property. Interestingly, however, none of these women live within easy access of their in-laws. In the average wealth category, sixteen of twenty-two (72.7%) women have more than one building; whereas six of the twenty-two (27.2%) have one building. This category is split by accessibility of in-laws (50%). In the wealthiest category, only three women (16.7%) have one building on their property whereas fifteen out of the 18 (83.3%) have more than one building present on the property. The majority of women in the wealthiest category have easy access to her in-laws home (61%) and seven of the 18 in this category do not have easy access to their in-laws home (39%). In Harar and Getanyamba, no families are in the poorest category. Those in the poorest wealth category live closer to town center and two live in the town center. 4.3 Maternal Biodemographics 4.3.1 Marriage Patterns: The Iraqw practice levirate marriage; one woman in the sample was married to the brother of her deceased husband. All of the other women were married and remained married throughout the duration of the project. Thirty-six women (81.8%) were their husband’s first and only wife. Five of the men had been divorced at least once prior to the current marriage (11.4%). Only two women (4.5%) were in polygamous marriages (Table 4.8).
Marriage Type N % Widow 1 2.3 First Marriage (both partners) 36 81.8 Second (or more) marriage for husband 5 11.4 Polygamous marriage 2 4.5
Table 4.8. Pattern of marriage for 44 of the participants.
4.3.2 Reproductive History: Women ranged in age from 18 to 32 years with an average of 25.0 years; ninety-five percent of the sample was between ages 20 and 30. Average
65 age at menarche and first pregnancy were 15.8 and 20.9 respectively. Twenty-four women (51%) had one living child at recruitment, eighteen women (38.3%) had two living children, and five women (10.64%) had three living children at recruitment. During the first interview, nine women (19.1%) reported experiencing at least one previous pregnancy loss, neonatal death, or infant death prior to the current pregnancy.
Variable N Mean SD Age 47 25.085 3.209 Height 47 158.5914.295 Gravidity 47 2.809 0.900 Parity 47 1.596 0.681 Age at Menarche 43 15.767 1.411 Age at First Pregnancy 46 20.913 2.866 Maternal Education 46 6.174 2.254
Table 4.9: Anthropometric and biodemographic data for women/mothers.
4.3.2.1 Pregnancy Sickness: Physical well being may affect caretaking practices and a woman’s ability to manage the household. A pregnancy sickness survey was conducted to assess whether symptoms experienced during pregnancy were associated with birth outcome. The following table summarizes symptoms experienced by women from a larger sample (n = 198) and from women participating in the study on birth transition (n = 47) (Table 4.10). The majority of women experienced dizziness and heartburn at some point in the pregnancy. Over half of the sample of felt nauseous, appetite loss, or weakness while pregnant. The sample of women participating in main part of the research project (n = 47), had similar experiences as the larger sample. Percentages are quite similar for each symptom. The exceptions were dizziness, joint pain and weakness; fewer women from the smaller sample experienced these symptoms.
66
Larger survey (n = 198) Sample survey (n = 47) Yes % Yes % Nausea 99 50.0 21 44.7 Vomit 74 37.4 18 38.3 Dizziness 146 74.1 32 68.1 Joint Pain 57 28.8 8 17.0 Appetite Loss 102 51.5 24 51.1 Weakness 103 52.0 18 38.3 Itchiness 30 15.1 6 12.8 Aversion to Smells 86 43.4 20 42.6 Heartburn 136 69.7 31 70.6
Table 4.10. List of pregnancy sickness symptoms and number and percentage of women who experienced the named symptom (n = 198) and the sub-sample (n = 47).
4.3.3 Maternal Anthropometry: The majority of women were measured at least twice before delivery and at least 5 times post partum. 4.3.3.1 Pregnancy Weight Gain: Rates of weight change increase in the latter part of pregnancy which is not unexpected as this is the time when pregnancy is most energetically expensive and when the fetus is becoming fat.
Measures Before birth N Mean SD Rate/day of weight gain 2nd Trimester 7th month – 6th month 1 2.95 0.069 6th month – 5th month 6 1.43 1.770 0.032 5th month – 4th month 13 1.696 0.861 0.031 3rd Trimester 4th month – 3rd month 24 1.094 1.098 0.036 3rd month – 2nd month 43 1.199 1.186 0.042 2nd month – 1 month 47 1.312 1.153 0.033
Table 4.11. Average weight change and average daily rate of change in the 2nd and 3rd trimesters of pregnancy and in the months post partum (B = birth).;
67 4.3.3.2 Body Mass Index: Body mass index (BMI) was calculated by dividing weight (kg) by height squared (m2) and monthly averages are presented in Table 4.12. The mean BMI score in the last month of pregnancy is 23.2 with a median of 22.8. BMI scores increase as the mother gains weight throughout the pregnancy. At birth, BMI scores drop as weight changes occur. After the immediate post partum, BMI score begin to increase again as women gain weight by eating lots of meat and fatty foods and while they are less active in the recovery period.
Measure Before Birth N Mean SD 2nd trimester 7 1 20.029 . 6 6 20.015 1.559 5 13 21.721 1.823 4 24 22.006 2.102 3rd trimester 3 43 22.398 2.486 2 47 22.675 2.679 1 47 23.321 2.724 Months after birth N Mean SD 1 45 22.214 3.024 2 45 22.282 3.171 3 44 22.184 3.276 4 43 22.389 3.336 5 42 22.027 3.562 6 17 21.523 3.064 7 2 21.418 5.237
Table 4.12. Average BMI scores in each month before and after birth (B = birth of newborn).
68 BMI scores are significantly different if women indicated that they did not have a household helper. BMI values were lower for those without enough help both before and after the birth of the newborn. In the two months before birth and in the five months after birth, the differences remain significant which may indicate the importance of household help during the birth transition (Table 4.13)
Monthly BMI - No SD BMI – SD U Chi- df p Measure helper Helper square -4 20.1 1.422.3 2.115.0 3.481 1 0.062 -3 21.6 1.922.7 2.78.0 1.152 1 0.283 -2 21.2 2.1 23.1 2.7 91.0 5.259 1 0.022 -1 21.6 2.5 23.6 2.7 100 4.536 1 0.033 0 20.3 2.522.2 2.16.0 2.885 1 0.089 1 20.1 2.4 22.4 2.5 89.0 5.800 1 0.015 2 20.0 2.0 22.8 3.0 60.0 8.048 1 0.005 3 20.2 2.4 22.8 3.1 81.0 6.213 1 0.013 4 20.2 2.7 22.8 3.3 90.0 5.020 1 0.025 5 20.3 2.7 22.8 3.3 83.0 5.557 1 0.018 6 20.2 3.322.6 3.579.0 2.450 1 0.118 7 20.3 4.521.8 2.916.0 0.941 1 0.332
Table 4.13. Results of Mann-Whitney U tests for differences in BMI based on availability of helpers before and after birth (shading indicates statistical significance).
69 4.3.3.3 Summed Skinfold Measures: As a measure of changes in body fat composition the sum of four skinfold measures is calculated by adding the raw measures of each of the four points (mid-upper arm or triceps, medial calf, subscapular, and midaxillary). While pregnant, summed skinfolds do not average above 50mm; in the seven months after birth, this average does not fall below 56mm (Table 4.14).
Months Before Birth N Mean SD 2nd trimester 7 1 48.990 6 5 40.8006.790 5 11 48.16816.244 4 22 50.51518.387 3rd trimester 3 42 49.44717.027 2 43 49.85919.674 1 45 46.77716.650 Months After Birth N Mean SD 1 45 62.63124.690 2 44 65.96625.086 3 44 65.69826.201 4 43 66.20126.520 5 40 66.70027.845 6 13 64.84416.713 7 2 75.16535.589
Table 4.14. Average of summed skinfolds in the months before and after birth (B = birth).
70 The presence of household help is significant in the post partum but is not associated with summed skinfold measures before birth. This pattern is different from that seen in BMI and bioimpedence measures of body fat, which show significant differences during pregnancy as well as in the post partum period (Table 4.15).
Monthly Skinfolds - No Measure helper Skinfolds -Helper U Chi-square df p -4 15.0 1.455 1 0.228 -3 25.2 31.1 23.0 3.573 1 0.060 -2 26.4 31.8 80.0 2.927 1 0.087 -1 26.4 32.4 111.52.684 1 0.101 1 24.2 32.2 85.5 5.972 1 0.015 2 24.6 32.6 61.0 7.884 1 0.005 3 24.7 32.4 80.0 6.355 1 0.012 4 24.0 32.5 93.5 4.590 1 0.032 5 23.1 32.5 78.0 6.256 1 0.012 6 24.1 31.8 69.0 3.660 1 0.056 7 23 30.4 18.0 0.530 1 0.467
Table 4.15. Results of Mann-Whitney U test results for differences in summed skinfold measures by presence or absence of household help (shading indicates statistically significant).
71 4.3.3.4 Body Fat: Body fat scores (%) as measured by a TANITA Body Fat Monitor/Scale show a steady increase in body fat throughout the pregnancy and the average was 31.6 ± 5.2% in the 9th month of pregnancy. After birth, average body fat percentages increase until approximately 5 months post partum. However, there is a great deal more variation in body fat percentages after birth than during pregnancy. This probably reflects diversity in post partum nutrition and access to post partum foods in addition to activity levels. Body fat percentage and summed skinfolds are strongly correlated in most months as shown by the correlation coefficient in Table 4.16.
Correlation Measure Before Birth N Mean SD Coefficient 2nd trimester 7 1 28.500 6 6 25.7504.547 0.747 5 13 30.2235.298 0.661 4 23 28.9355.501 0.727 3rd trimester 3 40 30.3755.166 0.754 2 46 30.4005.998 0.792 1 47 31.5855.326 0.608 Months After birth N Mean SD 1 45 30.8676.635 0.828 2 44 30.5396.459 0.826 3 44 30.7117.169 0.793 4 43 30.5407.065 0.784 5 42 29.8788.097 0.798 6 17 28.9157.217 0.836 7 2 31.2508.839 0.830
Table 4.16. Average body fat percentage before and after birth with correlation coefficient for body fat percentage and summed skinfolds.
The presence of a household helper translates into positive effects for the mother in the last trimester of pregnancy and for at least the first six months after the birth of the newborn. The presence of a household helper probably allows the mother to have more time resting than compared to mothers without a household helper (Table 4.17).
72
No helper SD Helper SD U Chi-square df p -4 23.5 3.7 29.5 5.0 11.5 4.364 1 0.037 -3 25.2 3.6 31.1 4.8 27.0 7.418 1 0.006 -2 26.4 5.3 31.8 5.2 75.0 5.779 1 0.016 -1 26.4 7.0 32.4 4.0 85.5 6.360 1 0.012 1 24.2 6.7 32.2 5.1 63.5 9.291 1 0.002 2 24.6 6.8 32.6 5.4 60.0 8.069 1 0.005 3 29.7 6.6 32.4 5.3 59.5 9.589 1 0.002 4 24.1 7.3 32.5 6.1 61.0 9.332 1 0.002 5 23.1 7.8 32.5 6.0 50.0 10.943 1 0.001 6 24.1 8.7 31.8 6.6 57.5 5.355 1 0.021 7 23.0 11.1 30.4 5.7 12.0 2.121 1 0.145
Table 4.17 Results of Mann-Whitney U test for differences in bioimpedence by presence or absence of household helpers (shading indicates statistically significant results).
4.3.3.5 Diet Breadth: Twenty-four hour dietary recall was collected for 248 days. Diets are relatively monotonous with maize meal (ugali) and maize porridge (uji) as stables. This is most often supplemented with beans, pumpkins, tomatoes, onions, and green leafy vegetables cooked in oil/fat. There were two major changes in diet associated with the birth of a newborn. The first is that only 12/146 (8.2%) reported eating meat before the birth of the newborn; and in the post partum period 52/102 (50.9%) reported eating meat. The opposite is true for green leafy vegetables; 106/146 (72.6%) reported eating greens before birth whereas 40/102 (39.2%) reported eating greens in the post partum period.
73 4.4 Index Children 4.4.1 Biodemographics: Biodemographic data are presented below for the index child. There were 28 (60%) females and 18 (40%) male index children who participated throughout the entire duration of this project. The average age (or birth space interval) of the index child at the birth of their younger sibling was 30 months (Table 4.18). The difference in the mean ages of male and female index children at the birth of the sibling was not significant (U = 206, Chi square = 1.322, 1 df, p = 0.250).
Birth Space Interval Mean age at birth of sibling (months) N % Mean SD Index children 47 29.998 9.9 Females 28 61.7 30.071 11.053 Males 19 38.3 29.891 8.197
Table 4.18 Average age of the index child at the birth of newborn sibling.
Fathers’ employment status is associated with differences in birth space intervals. Birth intervals are longest for women whose husband is primarily unemployed or not contributing to household production (40.1 months). Birth intervals for those whose husband are primarily farmers are 29.6 months and for those who primarily work for money it is 26.2 months. These differences are significant (Kruskal-Wallis = 8.319; p = 0.016, assuming chi-square distribution with 2 df). Mann-Whitney U tests indicate that the difference between farmers and those who work for money are not significant (U = 240, chi-square = 1.974, 1df, p = 0.160). However the differences between farming and not working are significant as are the differences between working for money and farming (Mann-Whitney U = 104.0; chi-square = 4.701, 1 df = 0.030 and U = 117, chi- square = 6.762, 1 df, p = 0.009). Mothers’ employment status was not associated with significant differences in birth space intervals (statistics not shown).
74 4.4.2 Breastfeeding 4.4.2.1 Weaning: Most children are weaned before the age of two and on average are weaned at 20.5 months. There is a difference in average age at weaning by sex but the difference is not statistically significant (U = 219, Chi square = 2.409, 1 df, p = 0.121) (Table 4.19). Age at Weaning N Mean (months)SD Index children 46 20.5 6.043 Females 27 20.2 6.710 Males 19 21.0 5.1
Table 4.19. Average age at weaning (months) for the index child.
4.4.2.2 Lactational Status at Conception of Sibling: Many women were breastfeeding into the next pregnancy and some women chose to continue lactating beyond the first month of the pregnancy (Table 4.20).
Lactational Status N = 46 % Female Male Not lactating at conception 13 28.3 9 4 Lactating into first trimester 21 45.7 14 7 Lactating into second trimester 9 19.6 4 5 Lactating into 3rd trimester 3 6.5 0 3
Table 4.20. Number and percentage of mothers lactating at various points across the birth interval.
75 There are no statistical differences in choosing to continue to breastfeed into the pregnancy by the gender of the index child (Table 4.21).
Overlap of Pregnancy and Lactation N Mean (months)SD Index children 46 2.0 2.1 Female 27 1.5 1.7 Male 19 2.8 2.5
Table 4.21. Average months of lactation into the next pregnancy.
The average age of index children who were not breastfeeding at conception is significantly different than those who were breastfeeding at conception. Those still breastfeeding were 26.9 (5.1) months old and those weaned before the next pregnancy were 40.5 (12.9) months old on average (Mann-Whitney U = 367.0; p = 0.000; chi-square = 13.843; 1 df). Therefore, this sample of 46 women may have captured fecund women and a few less fecund women with longer birth spacing intervals than the average for the rest of the sample. 4.4.2.3 Lactational Status and Maternal Social Network: Women who could rely on their mother-in-law for help weaned earlier than women who could not rely on their mother- in-law. Nineteen women did not cite their mother-in-law as a helper and 27 did cite her as a helper, their average age for weaning the index child was 24.2 months and 18.8 months, respectively. The difference is significant (Table 4.22).
Average age at weaning for SD U Chi- df p index child square Unable to Rely 24.16 6.0 380.0 7.644 1 0.006 Rely 18.82 5.5
Table 4.22. Results of Mann-Whitney U tests for differences in age of weaning for the index child by reliability of mother-in-law.
76
Reliance on the mother-in-law was not associated with lactational status at conception. This pattern seen in weaning, however, holds true for birth spacing intervals as well. Those who can not rely on their mother-in-law have longer birth intervals than those who can rely on her (34.7 vs. 26.5 months). This pattern makes sense given the data on the distribution of virilocal residence by village; those closer to the town center are less likely to be living near to relative. Women in the town center are also less active because they are not likely to be farming. In the town center, 7 out of 10 women weaned the index children before 18 months of age; each weaned due to the next pregnancy. In Harar and Getanyamba, approximately half of the women weaned the index child before 18 months of age. In sum, women with dependable mother-in-laws wean earlier and have shorter birth intervals than those who do not; and women who are less active (i.e., are not farming) have shorter birth intervals and wean earlier as well (Table 4.23).
Average birth interval SD U Chi-square df p Unable to Rely 34.71 6.0 410.0 11.728 1 0.001 Rely 26.52 5.5
Table 4.23. Results of Mann-Whitney U tests for differences in birth interval by mothers’ ability to rely on mother-in-law.
4.4.3. Growth:
4.4.3.1 Height and Weight of Sample by Age: Cross-sectional growth data are not locally available for this sample of children. In Appendix F, average recumbent length and weight are presented by age in months for this sample only (46 index children and 46 newborns/infants). Summaries of these results are presented below in Figures 4.2 and 4.3.
77 Recumbent Length by Age in Months
120 100 80 60 40 78 Length (cm) 20 0
3 1 7 9 1 5 14 2 2 33 3 45 5 57 6 Age (months)
Boys Girls
Figure 4.2. Recumbent length, cm of all children (index and newborn/infant) by age in months and sex. 78 Weight by Age in Months
20
15
10 79
Weight, kg Weight, 5
0 0 3 8 16202427303336395457 Age (months)
Boys Girls
Figure 4.3. Weight, kg of all children (index and newborn/infants) by age in months and by sex.
79 4.4.3.2 Height-for-age: Using the CDC 2000 as a reference population, average z-scores for height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) are plotted for the sample and by sex over the course of the birth transition for at least the four months before and four months after the birth of a sibling (Figures 4.4, 4.5. and 4.6). Over the nine monthly measures shown below, boys are shorter and lighter for their age than girls. This trend is evident in comparisons of WHZ with boys being a little lighter, or less robust for their height than girls. At quick glance there appears to be no changes in association with the birth of a new sibling. Upon closer inspection, a steady increase in HAZ occurs in boys beginning in the last trimester of the pregnancy and throughout the transition. For girls, the HAZ measures increase some, and slowly increase closer to the reference population mean for HAZ. Over the course of the transition, there is a general pattern of increasing HAZ but it usually remains below the mean by over 1 standard deviation with the exception of girls at four months post partum (Figure 4.4). In sum, boys tend to be shorter for their age than girls but increases at a steady rate from -2 SD to -1.5 SD. Girls are taller for their age than boys and by the end of the transition (at 4 months post partum) are less than 1 SD below the mean
80 Height-for-Age for Index Child during Birth Transition
0 -0.5 -1 -1.5 81 -2 -2.5 -4 -3 -2 -1 B 1 2 3 4 Monthly Measures (B = birth of sibling)
Index Children Boys Girls
Figure 4.4. Height-for-age (HAZ) for index children by monthly measures before and after the birth of a sibling.
81 4.4.3.3 Weight-for-age: Weight-for-age scores are different from the pattern seen in HAZ; over the birth transition, children become lighter for their age. Boys are even lighter for their age than girls. Throughout the third trimester, boys tend to become lighter. They reach a low point right at birth. After birth, boys remain between 1.5 and 1.25 SD below the mean. Girls are steadier throughout the transition and rather than being furthest from the mean at birth, they are closest to the mean at birth (Figure 4.5).
82 Weight-for-Age for Index Child during Birth Transition
0 -0.2 -0.4 -0.6 -0.8 -1 -1.2 Z-Score Z-Score
(CDC 2000) (CDC -1.4 -1.6 -1.8 83 -4-3-2-1B1234 Monthly Measures (B = birth of sibling)
Index Children Boys Girls
Figure 4.5. Weight-for-age by Monthly Measure Before and After the Birth of a Sibling
83 4.4.3.4 Weight-for-height: Throughout much of the transition, boys tend to be lighter for their height than do girls; the exceptions occur in 3 and 4 months before the birth of the sibling. Boys’ WHZ measures are nearly the same as the mean of the reference population. However, as the birth approaches, boys tend to get lighter for their height. Their scores fluctuate in the months after birth; there are slight declines in WHZ at birth and in months 2 and 4 post partum with slight increases in months 1 and 3 post partum (Figure 4.6). Girls are also below the mean of the reference population in WHZ z-scores. But instead of a staggered decline in WHZ at the birth of the sibling, they steadily become lighter for their height. Between birth and 4 months post partum, girls decline about .01 standard deviations each month. By the fourth month, they are nearly ½ of a standard deviation below where they started at the birth of the sibling. Boys’ decline is less dramatic; they only drop about .01 standard deviations in those four months but do increase by .02 standard deviations in months 1 and 3 post partum (Figure 4.6).
84 Weight-for-Height for Index Child during Birth Transition
0 -0.1 -0.2 -0.3 -0.4 -0.5 -0.6 85 Z-Score 2000) (CDC -0.7 -4 -3 -2 -1 B 1 2 3 4 Monthly Measures (B = birth of sibling)
Index Children Boys Girls
Figure 4.6. Weight-for-height for index child by monthly measure before and after the birth of a sibling.
85 4.4.3.5 Arm Circumference: Arm circumference measures for boys are just slightly smaller than girls throughout the birth transition which is consistent with the other types of measures presented above (Table 4.24). Both girls and boys follow a similar pattern over the birth transition. There is some decline before and at the birth of the sibling which is followed by a steady increase through the first four months after the birth of the sibling (Figure 4.7). These fluctuations are very minor and most simply reflect a general growth trend since the pattern does not follow that seen in WHZ calculations
86 MUAC 6BB 5BB 4BB 3BB 2BB 1BB Birth 1pp 2pp 3pp 4pp 5pp 6pp 7pp N 5 10 22 39 46 46 39 46 45 44 44 43 42 19 Index Children 15.1 14.7 14.7 14.6 14.7 14.6 14.8 15.0 15.1 15.3 15.5 15.7 15.6 15.7 Female 15.2 14.6 14.7 14.6 14.7 14.8 14.9 15.0 15.1 15.4 15.6 15.7 15.7 15.5 Male 14.9 14.8 14.7 14.4 14.7 14.6 14.6 14.8 15.0 15.1 15.3 15.7 15.4 16.1 Calf circumference 6BB 5BB 4BB 3BB 2BB 1BB Birth 1pp 2pp 3pp 4pp 5pp 6pp 7pp N 5 10 22 38 46 46 38 46 45 44 44 43 41 20 Index Children 18.7 18.4 18.3 18.3 18.3 18.6 18.7 18.7 19.1 19.2 19.4 19.7 19.8 19.6 Female 18.0 18.4 18.3 18.4 18.6 18.9 18.8 18.7 19.2 19.3 19.7 19.7 19.8 19.6 87 Male 19.0 18.5 18.3 18.2 18.1 18.5 18.5 18.8 19.0 19.2 19.6 19.8 19.8 19.8
Table 4.24. Changes in mid-upper arm and calf circumferences for the index child over the course of the birth interval (BB = before birth and PP = post partum.
87 Mid Upper Arm Circumference (MUAC) during Birth Transition
16 15.5 15 14.5 88 MUAC, cm MUAC, 14 13.5 -4 -3 -2 -1 B 1 2 3 4 Monthly Measures (B = birth of sibling)
Index Children Female Male
Figure 4.7. Monthly changes in mid-upper arm circumference for the index child over the birth transition.
88 4.4.3.6 Calf Circumference: Calf circumferences do not follow the same pattern as arm circumferences for either boys or girls (Table 4.24). Boys show a slight decline in the latter part of the mother’s pregnancy whereas girls’ calf circumferences are increasing slightly, peaking at birth and at one month after birth. After 1 month, both boys and girls show a steady increase in calf circumferences with girls’ measuring just slightly more than the boys (Figure 4.8).
89 Calf Circumference during Birth Transition
20 19.5 19 18.5 cm 18 17.5 90
Calf Circumference, 17 -4 -3 -2 -1 B 1 2 3 4 Monthly Measure (B = birth of sibling)
Index Children Female Male
Figure 4.8. Monthly changes in calf circumference for the index child over the birth transition.
90 4.4.4 Socioemotional Patterns: For an average 8 hour day, index children are scolded less than once, have two crying episodes, cry on average for 10 minutes, are comforted approximately 2 times and spend an average of 1.75 hours away from their mothers before the birth of their sibling. In the post partum, they are scolded less than once, average 1.5 crying episodes, cry on average for 8 minutes and are comforted one time. They spend approximately 2.5 hours away from their mothers (Table 4.25)
Socioemotional categories BB n PP n U test Chi-square df p Distance to mother 1.8 121 1.7 54 3335.0 0.049 1 0.825 Scolding episodes 0.8 125 0.7 57 3895.5 1.257 1 0.262 Crying episodes 2.3 125 1.3 61 5048.5 12.442 1 0.000 Crying, mins. 9.7 125 7.6 61 4381.5 2.748 1 0.097 Comforting episodes 2.1 123 1.2 57 4587.5 11.611 1 0.001 Without Mother, mins. 106.0 121 148.7 51 2279.0 7.763 1 0.007
Table 4.25 Results of Mann-Whitney U tests for differences in socioemotional patterns for index children before and after birth of the sibling (BB = before birth, PP = post partum; shading indicates statistically significant difference).
Before the birth of a sibling, the time boys and girls spend away from their mothers is significantly different. Boys spent approximate 142 minutes, 26.2% of the day, away from their mother in one day; whereas girls are without their mother for an average of 85.5 minutes, or 18.4% of the day (U = 2152.5, chi-square = 6.198, 1 df, p = 0.013). In the post partum period there are no significant differences when comparing socioemotional categories by sex. This included time spent away from mother; boys spent 132.4 minutes (23.6% of the day) without their mothers and girls spend approximately 160.1 minutes (or 35.5% of the day) with their mothers. The difference by sex is not significant (U = 237.0, chi-square = 2.229, 1 df, p = 0.135). Socioemotional patterns for boys do not seem to change much. However there are significant changes in socioemotional patterns for girls over the birth transition. Girls spend significantly more time away from their mothers in the post partum period whereas boys’ time spent away from mothers does not change significantly. Boys decrease from 26% to 23%. But, girls increase in percentage of time away from their mothers from 91 18% to 35%. The differences for boys are not significant but for girls are highly significant (Table 4.26).
N BB N PP U test Chi-square df p Distance to mother Boys 46 1.8 21 1.8 455.0 0.144 1 0.704 Girls 77 1.9 33 1.7 1331.0 0.397 1 0.529 Scolding episodes Boys 45 0.8 22 1.0 496.5 0.000 1 0.983 Girls 80 0.8 35 0.5 1609.0 2.011 1 0.156 Crying episodes Boys 45 2.3 24 1.7 639.5 1.659 1 0.198 Girls 80 2.4 37 1.1 2085.0 13.136 1 0.000 Crying, minutes Boys 45 11.1124 9.8 551.5 0.012 1 0.884 Girls 80 9.0 37 6.1 1876.5 10.620 1 0.033 Comforting episodes Boys 45 2.2 22 1.5 599.5 2.042 1 0.153 Girls 78 2.1 35 1.1 1876.5 10.620 1 0.001 Without mother Boys 44 142.521 132.4 491.0 0.166 1 0.683 Girls 77 85.5 30 160.1 652.0 12.252 1 0.000
Table 4.26. Results of Mann-Whitney U tests for differences in socioemotional patterns by sex (n = number of visits; BB = before birth, PP = post partum; shading indicates statistical significance).
Index children described as “adjusted” by the mother are not different by socioemotional pattern than children described as “still adjusting” (statistics not shown) except for one measure, average time spent crying. Girls who are “still adjusting” cry an average of 6.0 minutes whereas boys who are “still adjusting” cry an average of 9.7 minutes. The differences are significant (Mann-Whitney U = 338.0, chi-square = 4.469; 1 df; p = 0.035). 4.4.5 Summary: The majority of index children were still breastfeeding at conception of the newborn sibling. Weaned children were older than breastfeeding children. There were also differences in WHZ scores based on lactational status at conception. Those 92 index children who were weaned were older and the differences in growth reflect on age rather than reproductive status of the mother (decreasing HAZ, WAZ, and WHZ z-scores with increasing age). There are no significant changes in HAZ, WAZ and WHZ for index children as a group or by gender over the course of the birth transition. Socioemotional patterns change for girls, but not for boys. Girls cry less and spend more time away from their mothers in the birth transition. 4.5 Newborn/Infant Anthropometry 4.5.1 Birth outcome: Sex specific difference in the means is not significant for any birth outcome measure. On average newborns weighed over 3 kilograms, or a little less than 7 pounds, and were over 49.5 cm long (or 19.5 inches). These outcomes indicate that at birth Iraqw children have similar birth outcomes to reference population. They meet the mean for length and are slightly lighter in weight (Table 4.27).
93
Birth weight, grams N Mean SD Minimum Maximum Newborns 43 3085.814 393.545 2090 3820 Female 28 3116.071 329.448 Male 15 3029.333 500 Birth length, cm N Mean SD Minimum Maximum Newborns 43 49.712 1.914 46.0 57.2 Female 28 49.300 1.395 Male 15 50.48 2.504 Arm Circumference, cm N Mean SD Minimum Maximum Newborns 41 10.580 0.90 8.8 13.0 Female 26 10.612 0.858 Male 15 10.527 0.997 Calf Circumference, cm N Mean SD Minimum Maximum Newborns 41 10.780 0.771 8.9 12.6 Female 26 10.842 0.745 Male 15 10.637 0.830 Head Circumference, cm N Mean SD Minimum Maximum Newborns 42 34.743 1.382 32.1 39.5 Female 27 34.622 1.077 Male 15 34.960 1.833 Chest Circumference, cm N Mean SD Minimum Maximum Newborns 34 32.762 1.824 28.6 36.2 Female 20 32.085 1.770 Male 14 32.700 1.985 Ponderal Index N Mean SD Minimum Maximum Newborns 45 2.553 0.0326 1.672 3.304 Female 31 2.638 0.274 Male 14 2.362 0.360
Table 4.27. Newborn anthropometric measures at birth.
4.5.1.2 Gestational Age Estimates: Gestational age data were originally estimated by mother’s identification of her last menstrual period (LMP) because gestational age is a strong predictor of birth weight. Gestational age estimates based on mothers’ LMP were found to be unreliable in this sample. Others have used head circumference data to assess gestational age. For example, Wiley (1992) followed the suggestions by Miller and Hassanein (1971) using a head circumference of less than 31.2 cm to determine
94 prematurity. No newborn in the sample had a head circumference that small. Three newborns with a head circumference of less than 33 cm; although this is larger than the 31.2 cut-off suggested above, perhaps these newborns could be categorized as preterm when head circumference is considered with other measures as well. All three of these children had birth weights less than 2670 grams, or 2.6 kg. Two other newborns were less than 2670 grams but their head circumferences were greater than 33.5. If length is used as an indicator, two out of the three with small head circumferences had birth lengths of less than 47 cm. Ponderal index calculations suggest three of these newborns did not gain weight as much as is expected in the last trimester of pregnancy, thus were likely born preterm (Ulijaszek et al. 1998) (Table 4.28).
Birth Birth Head Gestational Age Ponderal Case Sex weight length circumference (LMP – 40 weeks) Index 149 M 2.670 51.0 32.8 ? 1.92 315 M 2.090 46.0 32.1 40 2.14 463 M 2.090 50.0 33.9 38 1.67 616 F 2.600 47.0 32.9 39 2.50 984 F 2.640 48.2 33.6 ? 2.35
Table 4.28. Anthropometric data for newborns suspected of being premature.
4.5.1.3 Maternal Biosocial Predictors of Birth Outcome: Although prepregnancy nutritional status would have been the ideal; other anthropometric markers are used when this information is not available (Krasovec and Anderson 1991; IOM 1990). Some maternal anthropometric variables are associated with the birth outcome measures which are described on Table 4.27. Often short stature can be used to assign a risk category for poor outcome (Krasovec and Anderson 1991). Two heights have been suggested as cut- off measures: 145 cm or 155 cm. The women in this sample average 158 cm with the shortest woman being 148 cm and 20% of the sample falling below the 155 cm cut-off suggestion (9/46 women). A Pearson correlation matrix shows a moderate association of maternal height (HTCM) to newborn birth weight (0.328; n = 46). When height is used as an independent variable predicting birth weight, height explains 8.7% of variation in 95 birth weights. A body mass index (wt/ht2) of less than 18.5 is generally used to predict poor outcome. No woman in this sample fell below this standard during pregnancy or in the 6 months after birth. Actual weights at the beginning of the third trimester (KBB3 and KBB2) are significant predictors and explain 9.2% of variation in birth weights for this sample of newborns; however, this prediction must be approached with caution because women could have been measured between 1 – 4 weeks before birth, thus rate of change may be a better variable. Weight gain from 3 to 1 month before birth (KILOBB3TO1), does not predict birth weight. Rate of weight gain in the last month of pregnancy (KR1) does not significantly predict birth weight of the newborn. The use of arm circumference as a screening tool for increased risk of poor outcome has also been suggested (Krasovec and Anderson 1991). Although several women in this sample fall below the recommended cut-off of 23.5 cm (n = 11), arm circumference measures in the second (MUAC-4) and third trimester (MUAC-1) did not predict birth weight (Table 4.29). These data suggest that women in this sample are not chronically malnourished and that approximately 10 - 15% of variation in birth weights can be explained by the nutritional status of the mother.
96
Code Independent Variable F p R2/Adjusted R2 HTCM Maternal height 5.314 0.026 0.108/0.087 KBB3 Weight, kg 3 months before birth 4.628 0.038 0.117/0.092 KBB2 Weight, kg 2 months before birth 7.89 0.008 0.158/0.13.8 KILOBB3TO1 Weight change, kg, from 3 months 3.568 0.067 0.093/0.067 BB to 1 month BB KR1 Rate of weight gain in last month of 3.540 0.067 0.076/0.055 pregnancy MUAC-4 Arm circumference 2nd trimester 1.001 0.330 0.050/0.000 MUAC-1 Arm circumference 3rd trimester 2.417 0.127 0.052/0.031 BIRTHSPACE Birth space interval , months 3.077 0.086 0.065/0.047
Table 4.29. Regression equations predicting birth weight from maternal nutritional status in second and third trimesters of pregnancy.
4.5.2 Newborn/Infant Growth This sample of newborns is compared to the CDC 2000 reference population for length- for-age (LAZ), weight-for-age (WAZ), and weight-for-length (WLZ) in the first seven months of life. 4.5.2.1 Length-for-age: The length of both boys and girls are the same as the reference population at birth, with boys being on average slightly longer than the girls (84.10). However, by four weeks of age, length is beginning to mover farther from the mean for both boys and girls and there is a steady decline in comparison to the reference means. Boys’ length is farther away from mean than the girls; and by seven months of age, the boys are nearly 2 standard deviations below the mean whereas girls are just 1 standard deviation below the mean (Figure 4.9).
97 Length-for-Age for Newborn
0.5 0 -0.5 -1 -1.5 -2 98
Z-Scores 2000) (CDC -2.5 B1234567 Monthly Measures (B = birth)
Newborns Girls Boys
Figure 4.9. Length-for-age for newborns/infants plotted monthly in reference to the CDC 2000 population.
99 4.5.2.2 Weight-for-age: Weight-for-age measures for all of the newborns at birth are more than ½ of a standard deviation below the reference population mean. But within the first month, the girls catch up to the reference mean and boys remain slightly below the mean for WAZ. Boys peak above the mean at 3 months after birth and are never again above the mean after 3 months. At 6 and 7 months after birth there is a sharp decline in WAZ and boys drop to over 1 standard deviation below the reference mean. Girls follow a different pattern when assessing WAZ changes after birth. Girls peak above the mean one month earlier than boys. At 2 months of age, they are almost a ½ of a standard deviation above the mean. They slowly decline, and at 5 months of age still remain above the mean. Boys have already fallen below the mean by 4 months of age. At six and seven months of age the girls have fallen below the mean. The changes are quite dramatic between the 6th and 7th months. Girls almost drop a ¼ of a standard deviation in 30 days and boys drop nearly ¾ of a standard deviation in 30 days (Figure 4.10).
100 Weight-for-Age for Newborns
0.5
0
-0.5
101 -1
Z-Score 2000) (CDC -1.5 B1234567 Monthly Measures (B = birth)
Newborns Girls Boys
Figure 4.10. Weight-for-age for newborns/infants plotted monthly in reference to the CDC 2000 population.
4.5.2.3 Weight-for-length: A comparison of weight-for-length (WLZ) z-scores shows that this sample of newborns is born at nearly ½ of a standard deviation below the mean of the reference population. Boys and girls do not follow the same pattern in the first 7 months of life. Boys start at 1.5 standard deviations below the mean and they remain below the reference mean until 2 months after birth. Boys’ WHZ z-scores peak at 6 months. Girls do not start out as far below the mean as the boys. Girls, like the boys peak at 6 months but were relatively heavier for their length compared to the boys throughout the first six months. However, this does not hold true in the 6 and 7 months; boys are heavier for their age than the girls, but only slightly (Figure 4.11).
102 Weight-for-Length for Newborns
1.5 1 000) 0.5 0 -0.5 -1 103 -1.5
Z-Score (CDC 2 -2 B1234567 Monthly Measures (B = birth)
Newborns Girls Boys
Figure 4.11. Weight-for-length for newborns/infants plotted monthly in reference to the CDC 2000 population.
Regardless of gender, there are significant differences in WLZ measures if the mother has a household helper. Household help is associated with WHZ scores that are closer to the mean of the reference population. This difference is significant at 3 and 6 months post partum (Table 4.30). Children in homes with a household helper had higher WLZ measures than children from homes without household help for the mother.
No helper HelperU Chi-squaredf p B -0.292 -0.705 195.50.313 1 0.576 1 month PP 0.257 -0.041 190.0 0.631 1 0.427 2 month PP 0.324 0.652 107.0 1.061 1 0.303 3 month PP 0.049 0.938 91.0 4.869 1 0.027 4 month PP 0.199 0.872 91.0 1.5531 1 0.231 5 month PP 0.241 1.031 116 2.281 1 0.130 6 month PP 0.383 1.196 91.0 4.152 1 0.042 7 month PP 0.298 0.830 25.5 1.855 1 0.173
Table 4.30. Results of Mann-Whitney U tests for differences in weight-for-length z- scores by presence or absence of household helpers (B = birth, PP = post partum; shading indicates statistically significant).
4.5.2.4 Summary for Newborns/Infants: The average age at weaning is approximately 21 months for this sample. A birth space interval below the average age at weaning is associated with a significant difference is birth weights of the newborns. There were five triads with a birth space interval less than 21 months. Their average birth weight was 2.852 kg. Triads with birth intervals greater then 21 months averaged a birth weight of 3.315 kg. Mann-Whitney U tests indicate the difference is significant (U – 37; p = 0.049, chi-square = 3.856; 1 df). Five out of five of the index children with intervals of less than 21 months were breastfeeding at the conception of their sibling.
104 CHAPTER 5
RESULTS II:
ASPECTS OF THE DEVELOPMENTAL NICHE
5.1 Introduction To address the questions asked in chapter one, statistical analysis are presented to discuss possible associations between behavioral factors and biological measures (Figure 1.2). Anthropometric measures and morbidity data are primarily treated as dependent variables and considered as a complex set of interacting, overlapping and competing processes mediated by biobehavioral factors. In this chapter, biobehavioral factors include variables described in Chapter 4 and collected from several surveys on social support, psychosocial well being, and family environment (see Appendix C for examples). The model presented in Chapter 1 is based on two other models that draw on several disciplines (Harkness and Super 1994; Millard 1994). The model by Harkness and Super (1994), stresses the role of the household as a mediator in the production of health. The model by Millard (1994) emphasizes the context of child mortality and organizes factors based on three tiers: proximate, intermediate, and ultimate such that the multiple causes of morbidity and mortality can be addressed. The model in Chapter 1 simplifies the synergistic relationships between members of a household and local ecology while at the same time providing an evolutionary rationale for the research (Figure 1.1).
105 5.2 Aspects of the Model Psychosocial well being, using the Hopkins Symptoms Checklist – 25, and support network data were collected to assess aspects of customs of care among women in this sample. The physical setting of the household is assessed by household size, composition, categories of wealth and employment status. The psychology of caretakers and the physical setting both influence, and are influenced by customs of care. These three variables ultimately define the developmental niche for children in a household. The child is an active participant in this process and her/his age, temperament, development, and ability to cope also influence the developmental niche and caretaking practices. Aspects of the model are tested below 5.2.1 Psychology of Caretaker 5.2.1.1 Pregnancy Sickness and Birth Outcome: Results of the pregnancy sickness survey indicate that birth weights are associated with two symptoms: joint pain and weakness (Table 5.1). For the sub-sample of 47 women participating in the pregnancy sickness survey, there were no significant differences in birth weight for any symptom. The only variable that approached significance was heartburn (U = 257; Chi-square = 3476; 1 df, p = .062).
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Mann- Birth Birth Whitney Chi weight weight U test square df p Symptom No Yes Nausea 2975.6 2809.9 5393.5 3.626 1 .057 Vomit 2929.7 2831.8 4916.0 2.234 1 .135 Dizziness 2946.7 2871.8 3684.0 0.469 1 .493 Joint Pain 2959.0 2728.0 4709.5 6.840 1 .009 Appetite Loss 2926.4 2861.0 4909.0 0.430 1 .512 Weakness 2976.8 2815.5 5414.0 3.896 1 .048 Itchiness 2996.3 2696.3 2990.5 3.777 1 .052 Aversion to 2905.9 2976.4 4882.0 0.683 1 .408 Smells Heartburn 2973.2 2853.5 4371 2.148 1 .143
Table 5.1. Results of Mann-Whitney U test statistics for differences in birth weight by symptoms experienced during pregnancy (No = did not experience this symptom; Yes = did experience this symptom).
The presence of joint pain and weakness are each associated with lowered birth weights in the larger sample surveyed. These two symptoms, joint pain and weakness, could indicate that the health of the mother is compromised. Since anemia is quite common among pregnant women in this area (22.7%) and joint pain is associated with many diseases (sickle-cell anemia, brucellosis, and malaria) (Hinderaker et al. 2001), it is possible that endorsement of this/these symptom(s) may actually represent non- pregnancy-related illness. Fisher’s exact test (two tail) of independence shows that joint pain and weakness are associated (n = 198; value = 5.330; p = 0.028; OR 2.102). Thirty- seven women who felt weakness also felt joint pain (which is 18.7% of the sample). Sixty-six out (33.3%) of one hundred and ninety-eight women experienced weakness without joint pain and twenty women (10%) felt joint pain without being weak. Women citing joint pain (n = 57) were twice as likely to cite weakness as well (37/57). 5.2.1.2 Anxiety and Depression: The Hopkins Symptoms Checklist – 25 is a commonly used instrument that includes psychological and physiological symptoms of anxiety and depression which offers potential for comparisons within and between populations (Beals
107 et al. 2003; Fischback and Herbert 1997; Kaaya et al. 2002; Wagner et al. 1999) (see Appendix D for questionnaire and translations). This instrument was used to assess levels of anxiety and depression among sub-groups of women in this sample. The average sum of the 25 questions on the survey was 43.6. Using a Kruskal-Wallis statistic to test for differences in average HSCL-25 scores by parity and gravidity did not indicate significant differences by these reproductive history variables (Table 5.2). A Pearson correlation of age and HSCL-25 scores was not statistically significant (-0.095). Linear regression also shows that age does not predict HSCL-25 scores (F = 0.420; 1 df; p = 0.520).
Kruskal-Wallis N Mean SD Rank sum test statistic df p Parity 45 0.917 2 0.632 1 44.375 2.988 579.0 2 42.188 3.659 328.0 3 44.6 6.546 127.0 Gravidity 45 0.622 3 0.871 2 42.789 3.384 426.5 3 41.750 3.688 372.5 4 41.875 5.215 182.5 5 49.5 10.431 59.5
Table 5.2. Mean scores from HSCL-25 by parity and gravidity.
Using general linear models with HSCL – 25 scores as the independent variable found that some nutritional markers were predicted from anxiety and depression scores. BMI in the last trimester of pregnancy was predicted by HSCL – 25 scores; interestingly, this is the time the survey was conducted. BMI at one month and three months post partum was not predicted by scores. Mid-upper arm circumference (MUAC), rate of weight change, bioimpedence, and summed skinfold scores were not predicted by HSCL – 25 scores (Table 5.3).
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F p R2/Adjusted R2 BMI 3 months BB 4.304 0.044 0.091/0.070 1 month PP 1.681 0.202 0.038/..015 3 months PP 0.849 0.362 0.019/0.000 MUAC 3 months BB 1.617 0.213 0.050/0.019 1 month PP 1.355 0.252 0.034/0.009 4 months PP 0.557 0.460 0.014/0.000 Rate of Weight Change 3 months BB 0.398 0.535 0.019/0.000 1 month BB 0.060 0.808 0.001/0.000 1 month PP 0.322 0.580 0.024/0.000 3 months PP 0.012 0.912 0.000/0.000 6 months PP 0.523 0.474 0.014/0.000 Bioimpedence 3 months BB 0.029 0.866 0.001/0.000 1 month PP 0.001 0.971 0.000/0.000 3 months PP 0.169 0.683 0.004/0.000 Summed Skinfolds 3 months BB 3.73 0.064 0.121/0.089 1 month BB 1.29 0.263 0.033/0.007 1 month PP 0.823 0.370 0.020/0.000 3 months PP 0.025 0.875 0.001/0.000
Table 5.3. Regression models for the effects of HSCL-25 (independent variable) on anthropometric measures (dependent variable) before (BB) and after birth (PP) (shading indicated statistically significant results).
109 Employment status of the woman indicates that there are differences in mean scores on the HSCL-25 assessment of anxiety and depression. Using nonparametric ANOVA, the differences are not significant (Kruskal-Wallis = 8.989; 5 df; p = 0.110). Women brewing beer (3) had the highest mean scores (68.0), and tailors (2) had the lowest mean scores (33.5) (Table 5.4).
N = 46 Mean SD Brew beer 3 68.0 21.6 Farm 23 40.1 11.9 Home 13 43.0 13.8 Market 2 52.0 12.7 Work 3 49.0 8.5 Sew 2 33.5 7.8
Table 5.4. Mean HSCL-25 scores by employment status of mother.
These categories are collapsed in Table 5.5. Women who sell fruit and vegetables, work for others or sew were combined into the category called “work for money”. A Kruskal- Wallis test shows that there are significant differences in mean scores by collapsed employment category (Kruskal-Wallis = 6.470; 2 df; p = 0.039).
Code Type Mean SD 1 Home 45.4 15.2 2 Farm 38.2 13.8 3 Work for Money 51.3 11.2
Table 5.5. Mean HSCL-25 scores and standard deviations by mother’s employment status.
110 Mann-Whitney U test statistics show that there is a significant difference in mean HSCL- 25 scores for those who primarily farm compared to those who primarily work to earn money. Mann-Whitney U tests comparing those at home to farming or those at home to working for money were not significantly different (Table 5.6).
Mann-Whitney Chi df p U statistic square Home x Farm 188.0 2.833 1 0.092 Home x Money 60.3 0.366 1 0.818 Money x Farm 53.0 5.558 1 0.018
Table 5.6 Results of Mann-Whitney U tests for differences in mean HSCL-25 scores by mothers’ employment status.
A woman’s employment status is associated with HSCL – 25 scores and there are differences in birth outcome (Kruskal-Wallis = 6.641, p = 0.036, with a chi-square distribution assumed with 2 df). Women who are primarily in the home (i.e., not farming as much) have the lowest birth weights but not the highest HSCL – 25 scores (45.4). Women who farm have the highest birth weights and the lowest anxiety and depression scores. Birth weights for women working for money are in the middle and their average HSCL – 25 scores are the highest. In sum employment is associated with both birth weights and HSCL – 25 scores (Tables 5.5 and 5.7). Mann-Whitney U test indicate the differences between birth weights from farmers and those working for money are significantly different. The differences between home and money and farm and money are not significant (Table 5.8).
Mean SD Birth weight Home 2.911 0.4 Farm 3.298 0.3 Money 3.111 0.4
Table 5.7. Average birth weight with standard deviation by mothers’ employment status.
111 Mann-Whitney Chi df p U statistic square Home x Farm 75.0 5.887 1 0.015 Home x Money 61.0 0.768 1 0.381 Money x Farm 144.0 1.973 1 0.160
Table 5.8. Results of Mann-Whitney U tests for difference in birth weight by mother’s employment status (shading indicates statistical significance).
When husband’s employment status is treated as a dichotomous variable determined by working (farm or money) or not working (none), women’s HSCL-25 summed scores are significantly different when nonparametric, Mann-Whitney U tests are employed (Mann- Whitney U = 203; Chi-square = 4.818; 1 df; p = 0.028) (Table 5.9).
N = 46 Mean SD Work 38 41.4 12.6 Not Working 7 55.6 18.3
Table 5.9. Mean summed scores for the HSCL-25 by husband’s employment status.
ANOVA results indicate that subdividing husband’s employment status is also associated with differences in mean HSCL-25 scores for women (Table 5.10).
N = 46 Mean SD Farm 18 36.9 Work 20 45.5 None 7 55.6
Table 5.10. Mean HSCL-scores for collapsed categories by husband’s employment status.
112 These differences are significant (F = 5.530; p = .007; R/R2 = 45.7/20.8); nonparametric ANOVA shows that the differences remain significant when sample size is considered and chi-square assumed (Kruskal-Wallis = 9.445; 2 df; p = .009) (Table 5.11).
Husbands’ employment status N Rank sum Farm 18 294.0 Money 20 510.0 None 7 231.0
Table 5.11 Kruskal-Wallis One-Way ANOVA for 45 cases; HSCL-25 scores by husbands’ employment status.
5.2.1.3 Major Worries: Women were asked to describe their major and daily concerns. Their self-identified concerns were recorded and categorized into four major stressors: economic, health, diet/nutrition and social. Women endorsing a particular stressor are listed as a “Yes” whereas women who did not endorse that particular stressor are listed as a “No”. Mean differences in HSCL-25 scores are presented in Table 5.10 for each self- identified stressor. Stressors that are shaded are significantly different based on Mann- Whitney U test statistics. Worries about cattle, milk, vurugu/fujo (the English translation includes disturbance, chaos, mayhem, breach of peace), marital communication/decision- making, and domestic violence indicate that scores are significantly different for women who endorse worrying about these specific concerns compared to those who do not worry about these concerns (Table 5.12).
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Stress No HSCL-25 Score Yes HSCL-25 Score p ECONOMIC N N Cattle 38 40.4 6 60.7 .005 No Savings 35 42.9 9 46.5 .55 Basic Needs 35 9 .01 Money 28 42.1 16 45.2 .16 Money for Medical Expenses 35 41.0 9 51.7 .06 Land 39 42.1 5 51.6 .58 No Employment 42 42.7 2 54.0 .30 No independent income 40 42.0 4 49.6 .55 Housing 41 42.6 3 51.3 .76
HEALTH Own Illness 43 1 .40 Others Illness 41 3 .15 STD 42 42.4 2 61.0 .78
DIET/NUTRITION Milk 41 42.1 3 58.7 .04 Hunger 32 43.1 12 50.0 .45
SOCIAL Vurugu/fujo 26 38.3 18 51.4 .004 Marital communication/ 34 41.5 10 49 .04 decision-making Violent Husband 40 40.9 5 65.4 .002 No Help 40 40.8 4 50.4 .08 Worry about Children 41 43.1 3 43.7 .54 Distance to Farm 43 43.1 1 48.0 .48 Inability to Work 42 40.4 2 60.7 .06 Family Relations 37 42.0 7 49.6 .35 Hard Work 41 43.2 3 42.7 .98 Beer and Alcohol 41 43.8 3 37.5 .72
Table 5.12. Mean HSCL-25 scores from sub-groups of women based on their daily worries (shading indicates statistical significance).
114 Principal components analysis was used as a post-hoc deductive method for evaluating the validity of the mental health questionnaire (modified HSCL) (Spector 1991). Principal components analysis serves as a data reduction technique for creating simpler sub-scales to assess depression, anxiety, and depression/anxiety (Kaaya et al. 2002). The sum of the entire scale was tested for internal consistency using Cronbach’s α coefficient and subscales were also tested for internal consistency (Cronbach and Meehl 1955; Spector 1991). Varimax rotation was used on sorted factor loadings. Unrotated and rotated factors were evaluated for differences and percent variance explained by each factor. Factors with eigen values below 1.0 and that explained ≤5% variation were omitted. Table 5.13 describes the list of symptoms in each subscale.
115
Factor Symptoms Variance Explained Factor Anxiety/Depressive Symptoms 17.6% 1 Heart races Anxious No way out Tightness in chest Lonely Blame oneself for things happening Discourage Factor Depressive Symptoms 9.7% 2 Feeling faint Thoughts of suicide Loss of strength Factors Depressive Symptoms 13.4% 3 No desire for things Do not feel important Troubling thoughts Can not do every day things Factor Anxiety 9.4% 4 Worry and unable to sit still Periods of great worry Cry easily or without reason Factor Somatic Symptoms 12.0% 5 Tremble No appetite Unable to sleep Feel afraid Headache
Table 5.13. Principle component analysis for subscales of the HSCL-25 with symptoms and variance explained.
116 For each of the daily worries listed by women, nonparametric statistics were employed to assess which factor (and its combination of symptoms) were significant. Only the daily stressors that were significant for that factor are shown on Table 5.14. Factor 5 was not significant for any worry; however, it approached significance for worries about STDs which may indicate that women likely to have STDs not only worry about the transmission but may be experiencing symptoms of the diseases which is why this factor is somatic in expression (U = 2.5; Chi-square = 3.796; 1 df, p = .051). Worries about cattle are significant for four factors. Vurugu/fujo is significant for two factors and domestic violence is significant for 2 factors. These worries will be revisited in Chapter 6.
Factor Worry P Mann-Whitney Chi df U test square 1 Anxiety/Depressive Symptoms No help .012 92.0 6.377 1 Basic needs .008 69.0 7.054 1 Money for medical .008 65.5 4.526 1 Marital communication/decision-making .019 99.0 5.471 1 Milk .037 17.5 4.342 1 Mother can’t work .025 2.5 5.04 1 Violent husband .001 10.5 10.583 1 Cattle .025 50.5 4.994 1 2 Depressive Symptoms Cattle .002 29.5 37.5 1 Vurugu/fujo .018 1.5 5.555 1 3 Depressive Symptoms Money .047 154.0 3.949 1 Milk .019 78.0 3.796 1 Cattle .007 37.5 4.339 1 4 Anxiety Cattle .037 56.5 4.339 1 Vurugu/fujo .018 1.5 5.555 1 Violent husband .009 29.5 6.893 1 5 Somatic Symptoms STDs .051 2.5 3.796 1
Table 5.14. Significant worries associated with each subscale.
117 5.3.1.4 Major Worries and Birth Outcomes: Maternal anthropometric measures associated with birth outcomes were presented in Chapters 4 and 5. Joint pain and weakness while pregnant were associated with lower birth weight (see Table 5.1). Maternal height and weight in the beginning of the third trimester also predicted birth weights. Taller and more robust women had heavier newborns (see Table 4.22). For each category of worry listed on Table 5.10, Mann-Whitney U statistics were used to test for differences in birth outcome. Four of the major worries were associated with differences in birth weight: cattle, vurugu/fujo, illness of others, and worries about money (Table 5.15).
118
Stress U testChi-square df p ECONOMIC Cattle 175.5 4.428 1 0.035 No Savings 74.5 0.050 1 0.822 Basic Needs 183.0 0.551 1 0.458 Money 304.5 3.861 1 0.049 Money for Medical Expenses 180.5 0.448 1 0.503 Land 124.5 0.998 1 0.318 No Employment 40.0 0.013 1 0.910 No independent income 68.5 0.221 1 0.639 Housing 72.0 0.239 1 0.625
HEALTH Own Illness 41.0 2.361 1 0.124 Others Illness 111.5 5.426 1 0.020 STD 41.5 0.001 1 0.978
DIET/NUTRITION Milk 77.5 0.556 1 0.456 Hunger 193.0 0.001 1 0.979
SOCIAL Vurugu/fujo 354.0 8.214 1 0.004 Marital communication/ 198.5 0.638 1 0.425 decision-making Violent Husband 167.5 6.707 1 0.010 No Help 186.5 0.018 1 0.892 Worry about Children 54.0 0.122 1 0.727 Distance to Farm 23.0 0.014 1 0.906 Inability to Work 71.0 2.637 1 0.102 Family Relations 124.0 0.031 1 0.860 Hard Work 81.0 0.825 1 0.364 Beer and Alcohol 65.5 0.035 1 0.852
Table 5.15. Mann-Whitney U tests for differences in birth weight by mothers’ worries (shading indicates statistical significance).
119 Worries about cattle, money, money for medical expenses and the illness of others had significant differences in the following birth outcome measures. Only significant results are presented. Most of these variables reflect measures of fatness. The exception is the worry about cattle, where height measures are compromised in addition to fat (Table 5.16).
U testChi-square df p Cattle Height-for-age 180.0 5.859 1 0.016 Weight-for-age 181.5 6.111 1 0.013 Height 175.0 5.071 1 0.025 MUAC 189.0 9.670 1 0.002 Calf circumference 168.5 5.508 1 0.019 Money Weight-for-age 292.5 4.230 1 0.035 Money for medical expenses Height 219.5 3.953 1 0.047 Calf 211.5 4.538 1 0.033 Illness of others Weight-for-age 105.0 4.606 1 0.032 Vurugu/fujo Weight-for-age 339.0 7.882 1 0.005 MUAC 293.5 5.650 1 0.017 Calf circumference 321.5 9.706 1 0.002 Violent Husband Height-for-age 157.5 4.932 1 0.026 Weight-for-age 168.5 6.899 1 0.009 MUAC 168.5 9.720 1 0.002 Calf circumference 168.0 8.631 1 0.003 Head circumference 171.0 7.424 1 0.007
Table 5.16. Statistically significant results for differences in birth outcome measures by mothers’ worries.
120 5.2.2 Support Network Several approaches were used to collect measures of women’s support networks. First, women were asked to free list categories of people that they could depend on in times of need. The following table summarizes the categories of individuals named by women (Table 5.17).
No Yes Husband 4 26 Mother in law 11 19 Father in law 20 10 In laws 5 25 Birth mother 7 23 Birth father 14 16 Uncle 23 7 Aunt 25 5 Brother(s) 14 16 Sister(s) 14 16 Neighbor 28 2
Table 5.17. Summary of members on mother’s list of those she can depend on in times of need (n = 30).
In another survey, I asked women to list specific individuals by name on which they could rely on in times of need. The total number of names on the lists ranged from 1 to 24 people. The average number of names was 8.1 (Table 5.18). When asked about how often they saw people on their list, means differed. The average woman saw two people from their list daily. In the month before the survey, most women saw at least one more person on this list. Overall, the women saw a mean of six people from their social network list.
121
Mean SD Total listed 8.1 4.9 See daily 2.7 2.2 Seen in last 2 weeks 3.8 4.3 Seen in last month 3.5 3.2 Seen total 6.9 3.8
Table 5.18. Mean number of people listed and mean number of people seen on that list over the course of one month.
There were five women who indicated that they could not rely on their in-laws and 25 women indicated that they could. Their HSCL – 25 summed scores are significantly different; acknowledgment of any other individual did not show significant difference in the mothers’ HSCL – 25 summed scores (Table 5.19).
U test Chi-squaredf p Husband 77.0 2.339 1 0.126 Mother-in-law 138.0 2.090 1 0.148 Father-in-law 122.5 0.985 1 0.321 In-laws 112.5 7.757 1 0.005 Mother 99.0 0.827 1 0.363 Father 135.5 0.960 1 0.327 Brother 156.0 0.827 1 0.067 Sister 124.0 0.250 1 0.617 Aunt 80.5 1.009 1 0.315 Uncle 94.5 0.474 1 0.491
Table 5.19. Results of Mann-Whitney U tests for differences in summed HSCL – 25 scores by individuals named on social network free lists.
5.2.3 Maternal Morbidity A mother’s health status assessed by self-reported morbid episodes may affect her ability to care for children. When a mother is ill, she may be less able to feed and care for children. With one exception (epilepsy), there were no women who reported suffering from severe diseases like tuberculosis or HIVAIDS. There were two women who were diagnosed with STDs and they reported that their husbands did not get 122 treatment and suspect they will continue to be infected. Almost all women were given ferrous sulfate when they attended clinics run by Haydom Lutheran Hospital. Unfortunately, assessments of anemia were not conducted in this study. On Table 5.20, the number of women who reported being ill in any given month are presented.
6BB 5BB4BB 3BB 2BB 1BB birth N 7 11 23 38 46 46 13 # of mothers ill 0 3 5 5 3 5 1 % 0.0 27.2 21.7 13.2 6.5 10.9 7.7 1pp 2pp 3pp 4pp 5pp 6pp 7pp N 46 45 44 44 44 44 39 # of mothers ill 4 9 6 7 6 3 4 % 8.7 20.0 13.6 15.9 13.6 6.8 10.3
Table 5.20. Number and percentage of women reporting illness in any given month throughout the birth transition (Pearson Chi-square = 7.39; df = 6; p = 0.243)
Pearson chi-square correlations indicate that there is no difference in the number of women reporting illness in the 3 months before and after birth. There is no difference in the proportion of women reporting their own illness either before or after birth; there is no trend suggesting that mothers are more vulnerable in late pregnancy or in the early post partum period. In Table 5.21, the types of illnesses experienced over the birth transition are described. The flu and malaria are the most common diseases reported. Because of Olsen et al.’s reported cerebral malaria was the most common indirect cause of maternal mortality it is interesting to note that the highest percentage of women reporting malaria, reported it in the first 3 months post partum.
123
N 2nd 3rd 1 – 3 months 4 – 6 months Trimester Trimester PP PP Diarrhea 6 1 0 0 5 Flu 6 1 0 1 4 Cold 16 4 4 3 5 Malaria 21 2 5 9 5 Skin infection 1 0 0 1 0 Cough 7 0 2 4 1 Other infections 6 0 1 2 3
Table 5.21. Types of illnesses experienced by mothers before and after birth of newborn.
5.2.4 Growing/Maturing Child (see Figure 1.2) 5.2.4.1 Temperament: Women were asked to describe the basic temperament of the index child to see if temperament played a role in the child’s level of acceptance of the newborn sibling (“adjusted” to the newborn or “still adjusting”). Local descriptions of child temperament usually fell into one of four categories (happy, quiet and shy, happy and outgoing, or outgoing); there was one anomaly whereby the mother described the child’s temperament as clever (Table 5.22).
N % Happy 17 37.8 Quiet and Shy 15 33.3 Happy and Outgoing 9 20.0 Outgoing 3 6.7 Clever 1 2.2
Table 5.22. Maternal descriptions of the child’s basic temperament.
Mothers were asked about the index child’s well being and reactions to the newborn in the first month after birth of the sibling. Women were asked to identify bouts of jealousy, affection, actions while breastfeeding the newborn, sleeping patterns, and personality changes. The first answer provided by every mother was that the index child loved the
124 newborn sibling. Observed interactions and maternal assessments of specific episodes of jealousy (defined as pulling at the newborn, poking at the newborn, hitting the newborn, or sulking in response to the mother’s interaction with the newborn), split the sample into two equal categories of adjustment. Fifty percent of index children were neutral or positive in their reaction to the newborn’s presence. The other half of the sample had negative behaviors associated with the newborn’s presence in at least the first month after the sibling’s birth (Table 5.23).
N % Adjusted 23 50 Still adjusting 23 50
Table 5.23. Categorization of index child’s well-being in the first month after birth of sibling.
Only one child was still acting jealous of the newborn 5 months after birth, but his mother said that he was improving and his jealousy was not as dramatic as compared to that occurring in the first two months. He was an extreme case when assessed as an individual. Child number 3C, was 22 months old when he was introduced to the newborn after his mother returned from Haydom Lutheran Hospital. His mother had only weaned him five months earlier. At first, he was curious about this newborn child and even a little scared of the newborn. Child 3C was told that he was a “big child” now and would have to act appropriately. He was supposed to sleep with his father now instead of his mother. Gradually, he came to realize that the child was going to stay and when he saw his mother breastfeeding the newborn, he became distraught. He tried pulling the newborn away and told his mother that the breast was for him, not the new child. He also requested that she throw this new child away. His other caretakers stepped in and distracted him and laughed at his “foolish” behavior. At the 30 day follow-up visit, Child 3C had lost nearly 1 kg of weight since the birth of his sibling. His mother said that he had been suffering from diarrhea for nearly 2 weeks. His grandmother laughed at him as he slumped to the ground after the measuring 125 session. She said his behavior had been foolish quite often this month. Interestingly, however, Child 3C never did go sleep with his father. In order to assess associations between personality and maternal perception of the index child’s well-being, I excluded the one child considered clever and tested for associations between happy (1), quiet and shy children into another category (2), and outgoing children (3) temperaments by adjustment to the newborn in a two way frequency table. The table showed that there is no association between the mother’s assessment of basic personality and her perception of the child’s well-being in the first month post-partum. Each temperament category was nearly evenly divided by “adjusted” and “still adjusting” (Table 5.24). It is interesting that 3/3 outgoing children are “still adjusting” and those adjusted are basically split between being happy and quiet and shy children.
126 Code Temperament N Adjusted Still adjusting Test Value df p 1 Happy 27 12 14 Pearson Chi-square 3.671 2 0.160 2 Quiet and shy 15 9 6 Likelihood ratio Chi-square 4.826 2 0.090 3 Outgoing 3 0 3 Cramer V 0.289
Table 5.24. Temperament categories used in a two way frequency table by index child’s adjustment to the newborn (“adjusted” and “still adjusting”). 127
Upon further reduction of the categories of temperament, I combine outgoing children and happy children into one category (1) because of their interactions are similar in response to the researcher and other guests; quiet and shy children are left in another category based on their initial responses to guests. The collapsed categories are not associated with adjustment category. In sum, there is no association between basic personality and maternal perception of the index child’s adjustment during the birth transition (Table 5.25).
128 Code Temperament N AdjustedStill adjusting Test Value df p 1 Happy and Outgoing 21 12 17 Pearson Chi-square 1.374 1 0.24 2 Quite and shy 23 9 6 Fisher exact 0.342 Odds Ratio 0.471
Table 5.25. Temperament categories used in a two way frequency table by index child’s adjustment to the newborn (“adjusted” and “still adjusting”) 129
CHAPTER 6
RESULTS III:
THE BIRTH TRANSITION
6.1 Introduction Transitions are a normal part of family membership (i.e., birth or death of individuals). Transitions are often associated with stress as social role changes occur that may, for example, affect the parent-child relationship (Teti et al. 1996). 6.2 Index Child and Growth Change throughout the Birth Transition It appears that girls are closer to the references standard mean than boys for height-for-age, weight-for-age, and weight-for-height (HAZ, WAZ, WHZ) throughout the birth transition (Figures 6.1 – 6. 3). However, at the beginning and end of the birth transition, they are nearly the same. Most differences occur in the middle of the birth transition although none of the differences are statistically significant, the pattern is interesting.
130 Height-for-Age for Index Child during Birth Transition
0 -0.5 -1 -1.5
Z-Score Z-Score -2 (CDC 2000) -2.5 131 -4 -3 -2 -1 B 1 2 3 4 Monthly Measures (B = birth of sibling)
Index Children Boys Girls
Figure 6.1. Height-for-age for index children during birth transition (B = birth of sibling).
Weight-for-Age for Index Child during Birth Transition
0 -0.2 -0.4 -0.6 -0.8 -1 -1.2 Z-Score Z-Score
(CDC 2000) (CDC -1.4 -1.6 -1.8 132 -4 -3 -2 -1 B 1 2 3 4 Monthly Measures (B = birth of sibling)
Index Children Boys Girls
Figure 6.2. Weight-for-age for index child during the birth transition.
132 Weight-for-Height for Index Child during Birth Transition
0 -0.1 -0.2 -0.3 -0.4 -0.5 133 -0.6 Z-Score (CDC 2000) -0.7 -4 -3 -2 -1 B 1 2 3 4 Monthly Measures (B = birth of sibling)
Index Children Boys Girls
Figure 6.3. Weight-for-height for index child during the birth transition.
133 6.2.1 Rate of Growth: In order to assess whether changes in weight gain are significantly different in the 3 months before birth compared to three months after birth, I had to control for rate change that normally occurs with age. I calculated the difference in weight change from 3 to 1 month before birth, and 1 to 3 months after birth. The difference in weight gain was divided by the reciprocal of the child’s age at 3 months before and 3 months after birth. By dividing one by the child’s age in months (i.e., reciprocal of age), the rate of change for younger children was slowed down and for older children, the rate of change was increased which essentially made rate of change by age irrelevant when paired t-tests were used to assess differences for individuals. Basically, rate of change was controlled for by age thus standardizing rate of change over the transition for each individual. Standard paired t-tests were used to test for changes in the rate of weight change over the course of the birth transition. The difference between the means was significant and it appears that rates of weight gain increases after birth (Table 6.1). This pattern does not hold true for stature. There is not a significant difference in rate of height change in the 3 months before birth as compared to 3 months after birth (p = .501; t = .679; SD = 58.3) (Table 6.1).
Code Variable Mean t-test df p Weight Change 2.863 35 0.007 BBKILO3TO1RE Rate of weight gain in 3 months 7.352 before birth PPKILO1TO3RE Rate of weight gain 3 months 15.161 after birth Stature Change 0.679 36 0.501 BBHT3TO1REC Rate of stature change in 3 51.739 months before birth PPHT1TO3REC Rate of stature change in 3 58.256 months after birth
Table 6.1. Comparisons of weight gain throughout the birth transition (shading indicates statistically significant).
134 After standardizing the data, paired t-tests show a similar pattern to the raw scores presented above. Z-scores for rates of weight gain z-scores are significantly different for children categorized as “adjusted” compared to children categorized as “still adjusting” (Table 6.2)
Code Variable N Mean t-test df p Still adjusting 19 4.934 18 0.000 BBKILO3TO1RZ Z-score of weight gain in 3 0.858 months BB PPKILO1TO3RZ Z-score of weight gain 3 -0.093 months PP Adjusted 17 1.380 16 0.186 BBKILO3TO1RZ Z-score of weight gain in 3 0.475 months BB PPKILO1TO3RZ Z-score of weight gain 3 0.051 months PP
Table 6.2. Comparisons of z-scores for rate of weight gain for index child by adjustment category (BB = before birth, PP = post partum; shading indicates statistical significance).
It is possible that categorization of the child by the mother may be a reflection of her assessment of the child’s overall health through fat. Mothers would often comment on the healthiness of an individual based on their robustness; fat is equated with healthiness. Thus, I think children were categorized by mothers based on the mother’s assessment of the child’s fat; probably more so than on changes in behavior among other reasons. Perhaps mothers would categorize children based on their health status as well because mother’s reported more illness in the months post partum (discussed below). Most of the time, the child focused on by the mother was the most recently weaned child (index), but her choice is dependent on her assessment of each child in that moment. It was quite common to see a mother pull the index child toward her and say “eat my food” even though the mother expects each child to become more mature and independent with the birth of a new sibling (regardless of age). The buffering of some children was reflected in rates of weight gain. Those children the mother identified as “still adjusting” (hajazowea bado) were the children 135 who received more food in the months following the birth of a sibling. This result was contrary to expectations. I expected the children identified by the mother as “adjusted” (amezowea) to have HAZ, WAZ, and/or WHZ scores closer to the reference mean than the adjusting children (Figure 6.4). In sum, mothers’ post partum assessment of the index child’s adjustment to the newborn was not reflected in any measure of growth except in the first 3 months post partum. Children categorized by the mother as “adjusted” had a daily rate of weight gain of .001 grams, whereas children she categorized as “still adjusting” had a kilo rate weight gain of .012 grams in the first three months post partum. This difference is statistically different (Mann-Whitney U test statistic = 79.0, Chi – 10.651, 1 df, p = .001). Perhaps the children mothers categorized as “still adjusting” were ones she more worried about and were subsequently fed extra food. This may explain why their rate of weight change is faster in the first three months than children less worried about.
136
Weight-for-Height by Maternal Perception of Adjustment in Birth Transition
0.2 0 -0.2 -0.4 -0.6 137 -0.8 -1 -1.2 Z-Score (CDC 2000) (CDC Z-Score -4 -3 -2 -1 B 1 2 3 4 5 6 7 Monthly Measure (B = birth of sibling)
Well adjusted Adjusting
Figure 6.4. Weight-for-height by maternal perception of adjustment in the first month of the birth transition.
6.2.2 Morbidity 6.2.2.1 Index Children: The following data provide information on monthly reports of illness for both index children and newborns/infants (mothers’ morbidity is presented in Tables 5.15 and 5.16). Mothers were asked to remember illnesses experienced by their children each month. Types, duration, severity of illness were recorded. The percentage of index children the mother reports as ill remains relatively consistent throughout the months before birth. There is a trend for increased reports of illness in the first two months after birth (Table 6.3). Either a child experiences an increased number of bouts of morbidity after the birth of a sibling or mothers are more attuned to their children as they are spending much of this time resting, and thus report more illness because they have more time to think about their children while they are in a period of rest. Another reason may be that mothers are simply more worried about their children’s well being in the post partum period. Thus, this trend may be a reflection of their worries about the index child as the child’s sleeping arrangements have changed and they are often being cared for by others during these first two months.
138
6BB 5BB4BB 3BB 2BB 1BB birth N 6 11 23 39 45 45 37 # of index children ill 2 1 6 11 8 11 3 % 33.3 9.1 26.1 28.2 17.8 24.4 8.1 1PP 2PP 3PP 4PP 5PP 6PP 7PP N 41 42 44 42 44 42 20 # of index children ill 13 15 11 12 12 6 6 % 31.7 35.7 25 28.6 27.3 14.3 30.0
Table 6.3. Number and percentage of index children ill through birth transition (BB = before birth, PP = post partum).
The following table is a summary of the types of illness experienced by index children and newborns/infants; it is divided into four time categories (2nd and 3rd trimester and months 1 -3 and 4 – 6 post partum) rather than exact months. For index children, they experience colds, malaria, coughs, flu and diarrhea most often (Table 6.4).
139 N 2nd 3rd 1 – 3 months 4 – 6 months Pearson Chi- df p Trimester Trimester PP PP square value Index Diarrhea 10 0 3 3 4 Eye infection 2 0 0 2 0 Flu 11 0 1 3 7 7.364 1 0.007 Cold 39 4 8 19 8 5.769 1 0.016 Malaria 21 3 7 6 5 Fever 1 0 1 0 0 Skin infection 4 0 1 1 2 Cough 16 2 7 3 4 Other infections 4 0 1 2 2 Newborn
140 Diarrhea 11 NA NA 2 9 Eye infection 3 NA NA 2 1 Flu 14 NA NA 4 10 Cold 25 NA NA 13 12 Malaria 14 NA NA 9 5 Fever 3 NA NA 2 1 Skin infection 1 NA NA 0 1 Cough 17 NA NA 5 12 Ear infection 2 NA NA 0 2
Table 6.4. Maternal reports of types of illnesses experienced by index children and newborns/infants (shading indicates a significant difference of reporting before and after birth of sibling).
As reported in Chapter 5, the number of women ill remains constant with no illness occurring more often before or after birth (Table 5.15 and Table 5.16). For the index children, a Fisher exact test (two tail) shows that over the course of the 12 months (6 before the birth of a sibling and 6 after the birth of a sibling); there is no association between reported illness occurring before or after birth (Pearson Chi-square value = 3.467, 1 df; p = 0.063; fisher exact p = 0.071; OR 1.498). However, a narrower birth transition of six months, comparing the 3 months before birth to the 3 months after birth shows that mothers are more likely to report in the 3 months post partum. Index children are 1.7 times more likely to be reported as sick in the first three months post-partum than during the last trimester of the mother’s pregnancy (Pearson Chi-square value = 4.315, 1 df, p = 0.038; fisher exact p = 0.043; OR 1.748). Furthermore, the index child is more likely to suffer from colds or the flu in the post partum period. For example, reports of colds are quite high in the first 3 months after birth as compared to other times throughout the birth transition and reports of flu are higher in the 4 -6 month post partum period which is similar to that seen in newborns and mothers; these associations are statistically significant (Table 6.4). Additionally, the duration of illness is different while the mother is pregnant as compared to the post partum period. Mann-Whitney U test statistics show that the average number of days reported as ill (duration of illness) is significantly different before birth as compared to after birth (Figure 6.5)
141 Mean Duration of Illness in Birth Transition
12 5.8±3.4 8.0±5.0/7.4±5.3 10 8 6 142 4 2 0 Mean Duration (days) -6-5-4-3-2-1B1234567 Monthly Measure (B = birth of sibling)
Index Child Newborn
Figure 6.5. Mean duration of illness for index children (blue) and newborn/infant (red) by month throughout birth transition..
For the index child, adjustment category (adjusted vs. still adjusting) was not reflected in episodes of morbidity. Children who are “adjusted” are no more likely to become ill than children who are “still adjusting” (Pearson chi-square value = 0.061, 1 df, p = 0.806; fisher exact p = 0.825; OR = 0.947). Temperament is not reflected in episodes of reported morbidity. It is possible that these simple categories are not refined enough to capture individuality in response and detailed temperament assessment would be difficult but useful for understanding the child’s role as a participant in her/his developmental niche. 6.2.2.2. Newborns/Infants: In the first month, only a few newborns were reported to be ill by mothers (Table 6.5).
1PP 2PP3PP 4PP 5PP 6PP 7PP N 46 43 41 43 42 42 20 # of newborns ill 5 13 14 15 19 14 14 % 10.9 30.234.1 34.9 45.2 33.3 70.0
Table 6.5. Number and percentage of newborns/infants reported as ill after birth
Reports increase in the second month which remains consistent until about the 7 months after birth. Many women began supplementing the infant’s diet in the second and third months after birth and by the third month after birth many women had returned to their full work schedule. It is also interesting to note that in the 7th month post partum, there is an increase in the percentage of infants reported as ill. This coincides with a definite need for nutritional requirements beyond breast milk; breast milk alone after six months of age is insufficient. Although in most months less than 30% of the participants were ill, the average number of days ill per month varied from less than 4 to 9.5 (see Figure 6.1) It is interesting to note that reported incidence of diarrhea, flu and respiratory infections occurs more often in the 4 – 6 month category for newborns; perhaps a consequence of supplementation and reduced breastfeeding and increased mobility. Zeitlyn et al. (1995) point out that incidence of diarrhea is associated with increased
143 activity and exploration associated with crawling and increased mobility in general. Wiley and Pike (1998) point out that models of developmental stage may be more reflective of risk because the dynamics between the individual and her/his local ecology are emphasized and children develop at different rates. Although I only collected information on supplementation from 14 mothers, the pattern shows that early supplementation is common and it is rarer to exclusively breastfeed for the first six months. One reason for supplementation may be that women return to work duties in the second month post partum (Table 6.6). Two women expressed concerns about insufficient milk supply and the subsequent need for early supplementation.
144 Month Actual Number of newborns/infants Total % Actual Number of women Total % supplemented by month (n = 14) supplemented returned to work by month returned (n = 12) 1 3 3 21.4 5 5 41.7 2 4 7 50.0 4 9 75.0 3 2 9 64.3 2 11 91.7 4 4 13 92.8 0 11 91.7 5 0 13 92.8 1 12 100 6 1 14 100 NA NA NA
Table 6.6. Month of supplementation for newborns and return to work for mothers.
145
6.3 The Triad Figure 6.6 is a summary of body composition changes for the triad over the course of the birth transition. Body composition is plotted as changes in BMI for mothers; whereas the index and newborn are plotted as their average WHZ scores taken from the CDC 2000.
146 Changes in Body Composition
1.2 0.9 0.6 0.3 0 -0.3 147 -0.6 -0.9 Weight-for-Height Z- Weight-for-Height Score (children) and and (children) Score -1.2 BMI changes (mother) -4 -3 -2 -1 B 1 2 3 4 5 6 7 Monthly Measure (B = Birth of Sibling)
Index Newborn Mom BMI Change
Figure 6.6. Changes in body composition for the triad. Index child and newborn presented as weight-for-height z-scores and mothers as changes in BMI.
The mother and newborn have parallel changes in the first two months after birth which are similar to results from La Paz, Bolivia presented by Novotny and Haas (1987), and among the Turkana, Kenya presented by Gray (1992), among others. Both mother and newborn show increases in fatness, but as a group the index children do not. . Cultural rules require that women who just gave birth eat meat and fatty foods. Regardless of wealth category, every woman in this sample ate some meat in the post partum period. A woman is six times as likely to be in the post partum period if she is eating meat. In these first two months post partum women are essentially force fed; they eat a lot of meat and fatty foods which is reflected in their summed skinfolds which during pregnancy average below 50 mm and in the post partum months do not fall below 56 mm. It was not unusual for women to weigh more in the first or second month post partum than they did in the 9th month of the pregnancy. As expected, infants peak in WLZ at six months of age. Maternal changes in BMI fluctuate quite a bit in the months post partum but show a drop at about the time the mother returns to doing many of her work duties which is approximately 2 months post partum. The infant parallels this change slightly as WLZ scores flatten some in months 2 to 4; it is similar to the pattern seen in BMI for mothers. Mothers’ BMI scores markedly drop off after the newborn is six months of age; it is at this time that Iraqw children begin a steady decline in WHZ measures. Newborns at six months of age are approximately ½ of a standard deviation above the mean. Children tend to remain above this mean until approximately 22 months of age at which time, WHZ measures tend to fall below the mean. This change also coincides with the average age at weaning which is estimated 21 months of age. Index children do not have dramatic changes in their WHZ scores. They remain relatively stable across the birth transition although their scores are consistently declining. It appears that as a group the benefits of the post partum diet are not reflected in WHZ z-scores in the first two months after birth as is seen in mothers and the newborns. Over the course of the year, the average WHZ z-score for index children falls by nearly 1 standard deviation. However, in the first two months after the birth of a sibling there were neither dramatic increases nor decreases in WHZ for the index child.
The social role change from youngest, breastfeeding child to older weaned sibling is not reflected in these means plotted in Figures 6.1 – 6.3 and 6.6. When the sample is assessed by sex and adjustment category, the potential patterns of nutritional buffering become more apparent (Figures 6.7 and 6.8). Both male and female index children who the mother categorized as “still adjusting” had higher WHZ scores before the birth of the sibling compared to those the mother categorized as “adjusted”. Boys who were used to the presence of a newborn sibling showed increases in WHZ scores in months 1 and 2 post partum. Those boys accustomed to the presence of a newborn decreased in WHZ measures but by the third month showed a moderate increase. This increase may be explained by nutritional buffering by mothers. Girls who were “still adjusting” had higher z-scores than girls who were “adjusted” throughout most of the transition. By the seventh month post partum both boys and girls who were “still adjusting” showed lower WHZ scores than those who were used to the newborn right away. Girls who are “adjusted” (n = 11) do not have a significant change in rate of weight gain; whereas girls who are “still adjusting” (n = 9) show an increased rate of weight gain in the first three months post partum period. This does not hold true for boys. All boys, regardless of adjustment category have a significant increase in rate of weight gain in the post partum period. However, the differences in rate of weight gain for those boys categorized as “adjusted” is less than that of those labeled as “still adjusting”, but the difference is not statistically significant (11.3 vs. 16.3).
149
Weight-for-Height for Male Index Children by Adjustment Category
0.5
0 -0.5 150 -1 -1.5 Z-Score 2000) (CDC -4-3-2-1B1234567 Monthly Measure (B = birth of sibling)
Boys A Boys SA
Figure 6.7. Weight-for-height z-scores for male index children by adjustment category (A = adjusted; SA = still adjusting).
Weight-for-Height for Female Index Children by Adjustment Category
0.5
0 -0.5
151 -1 -1.5 Z-Score 2000) (CDC -4 -3 -2 -1 B 1 2 3 4 5 6 7 Monthly Measures (B = birth of sibling)
Girls A Girls SA
Figure 6.8. Weight-for-height for female index children by adjustment category (A = adjusted; SA = still adjusting). 151 CHAPTER 7
RESULTS IV:
REPRODUCTION AND SOCIAL CONTEXT
7.1 Introduction Worries of cattle, milk, marital communication/decision-making, vurugu/fujo and domestic violence represent three major aspects of women’s lives: economics (cattle), hunger (cattle and milk), and social relations (vurugu/fujo, domestic violence, and marital communication/decision-making). Each of these major worries may be associated with feelings of uncertainty. As women are primary caretakers of children, they are responsible for nutrition, health, and education. Among the Iraqw successful motherhood gives women the power of moral authority over all others in society (Snyder 1993). When avenues to successful motherhood are threatened, women will experience feelings of uncertainty and vulnerability; and risks for poor outcome tend to be context specific (Allen 2002; Kent 1991; Kilbride and Kilbride 1990). 7.2 Cattle and Milk 7.2.1 Maternal: Cattle and milk can either represent worries about the economy or worries about ability to feed one’s children. Cattle are often treated as a “bank” because one cattle is typically worth approximately 100 USD. Cattle, of course, provide milk which is considered an important food source for the Iraqw, especially for children. Differences in maternal body composition measures are not significantly different for women who worry about cattle (n = 6) and milk (n = 3) compared to those who do worry about cattle (n = 38) and milk (n = 41) (Table 7.1).
152 Two out of the three women who cited worrying about milk also cited worrying about cattle; however these variables will be treated separately because the categories represent the words chosen by the mothers when asked to free list their worries (see Table 5.10).
Mann-Whitney Chi- df p U test square CATTLE BMI 119.0 0.029 1 0.864 Summed skinfolds 116.0 6.031 1 0.861 Bioimpedence 135.5 0.739 1 0.390 MUAC 120 0.224 1 0.636 Calf circumference 97.5 0.224 1 0.636 Rate weight change 3 months BB 23 0.648 1 0.827 Rate of weight change 1 month PP 31 3.521 1 0.061 Land owned 14 0.615 1 0.433 Land farmed 18 2.216 1 0.137 Social Support 53.0 4.342 1 0.037 Total names on social network 51.5 5.235 1 0.022 MILK BMI 66.0 0.001 1 0.981 Summed skinfolds 60.5 0.044 1 0.834 Bioimpedence 62.5 0.014 1 0.905 MUAC 64.0 0.036 1 0.849 Calf circumference 58 0.009 1 0.924 Rate weight change 3 months BB 29 0.762 1 0.383 Rate of weight change 1 month PP 8 0.054 1 0.817 Land owned 14 0.615 1 0.433 Land farmed 18 2.216 1 0.137 Social support 27.0 2.096 1 0.148 Total names on social network 27.0 2.826 1 0.093
Table 7.1. Results of Mann-Whitney U tests for biosocial differences for women who worry about cattle and milk compared to those who do not worry about these concerns (BB = before birth, PP = post partum).
7.2.2 Children 7.2.2.1 Index Children: Women’s worries about cattle are reflected in growth z-scores for the index children (compared to CDC reference population). Index children whose
153 mother worries about cattle (n = 6) show significant differences in HAZ and WAZ z- scores; WHZ is not significantly different compared to index children whose mothers do not worry about cattle (n = 38). This pattern holds true across the birth transition. It is difficult to ascertain whether this is primarily an economic concern or primarily nutritional. If women worrying about cattle are economically constrained, they may not be able to access the healthcare system as readily as others. These concerns may also represent women who can not provide the types of foods they would like to feed to their children. Most likely, it is a combination of the two that explains such differences (Table 7.2)
Mann-Whitney Chi- df p No Yes U test square 3 months BB Height-for-age -1.605 02.822 135.0 4.413 1 0.036 Weight-for-age -1.210 02.516 134.5 5.043 1 0.025 Weight-for-height -0.057 -0.476 103.5 0.823 1 0.364 1 month PP Height-for-age -1.424 02.965 179.5 5.019 1 0.025 Weight-for-age -1.172 -3.013 179.5 5.026 1 0.025 Weight-for-height -0.216 -1.087 146.0 1.198 1 0.274 3 months PP Height-for-age -1.113 -2.426 158.0 5.699 1 0.017 Weight-for-age -0.988 -2.762 154.0 4.999 1 0.025 Weight-for-height -0.360 -1.438 120.0 0.897 1 0.343 6 months PP Height-for-age -0.982 -2.420 162.0 8.229 1 0.004 Weight-for-age -0.997 -2.844 149.0 5.526 1 0.019 Weight-for-height -0.562 -1.624 122.0 1.677 1 0.195
Table 7.2. Results of Mann-Whitney U tests for growth differences in index children by those with mothers who worry about cattle compared to those with mothers who do not worry about this concern (BB = before birth, PP = post partum; shading indicates statistical significance).
The z-scores for the three children whose mothers cited milk as a worry were not significantly different from the children whose mothers did not cite milk as a worry (Table 7.3). 154
Mann-Whitney Chi- df p No Yes U test square 3 months BB Height-for-age -1.769 -1.610 33.5 0.050 1 0.824 Weight-for-age -1.384 -1.355 37.5 0.010 1 0.922 Weight-for-height -0.115 -0.055 35.0 0.004 1 0.948 1 month PP Height-for-age -1.618 -1.860 71.5 0.217 1 0.641 Weight-for-age -1.334 -2.650 74.0 0.339 1 0.560 Weight-for-height -0.235 -1.690 66.5 0.054 1 0.816 3 months PP Height-for-age -1.437 -1.803 69.0 0.184 1 0.660 Weight-for-age -1.285 -1.693 69.0 0.184 1 0.668 Weight-for-height -0.387 -0.440 66.5 0.096 1 0.757 6 months PP Height-for-age -1.253 1.440 74.0 0.724 1 0.395 Weight-for-age -1.142 -1.890 76.0 0.905 1 0.341 Weight-for-height -0.429 -1.230 77.5 1.054 1 0.305
Table 7.3. Results of Mann-Whitney U tests for growth differences in index children by those with mothers who worry about milk compared to those with mothers who do not worry about milk (BB = before birth, PP = post partum).
7.2.2.2 Newborns/Infants Newborns follow a similar pattern to that for index children. Length-for-age (LAZ) and weight-for-age (WAZ) z-scores are significantly different, whereas weight- for-height (WLZ) z-scores do not differ based on worries about cattle (Table 7.4)
155
Mann-Whitney Chi- No Yes U test square df p Birth Length-for-age 0.105 -0.638 180.0 5.859 1 0.016 Weight-for-age -0.523 -1.340 181.5 6.111 1 0.013 Weight-for-length -0.594 -0.627 131.5 0.516 1 0.472 1 month PP Height-for-age -0.087 -1.482 191.5 7.026 1 0.008 Weight-for-age 0.095 -1.095 188.5 6.494 1 0.011 Weight-for-length 0.055 -0.030 107.5 0.224 1 0.636 3 months PP Length-for-age -0.411 -1.472 169.0 7.862 1 0.005 Weight-for-age 0.402 -0.806 145.0 3.590 1 0.058 Weight-for-length 0.752 0.354 118.0 0.759 1 0.384 6 months PP Length-for-age -0.980 -2.016 146.5 5.068 1 0.240 Weight-for-age 0.084 -1.522 143.0 4.460 1 0.035 Weight-for-length 1.118 0.082 127.0 2.173 1 0.140
Table 7.4. Results of Mann-Whitney U tests for growth differences in newborns/infants by those with mothers who worry about cattle compared to those who do not worry about this concern (BB = before birth, PP = post partum; shading indicates statistical significance).
As is true for index children, worries about milk are not reflected in growth z- scores for newborns/infants (Table 7.5)
156
Mann-Whitney Chi- df p No Yes U test square Birth Length-for-age 0.035 -0.045 33.5 0.050 1 0.824 Weight-for-age -0.590 -1.257 37.5 0.010 1 0.922 Weight-for-length -0.573 -0.937 35.0 0.004 1 0.948 1 month PP Length -for-age -0.255 -0.573 71.5 0.217 1 0.641 Weight-for-age -0.023 -0.677 74.0 0.339 1 0.560 Weight-for- length 0.078 -0.393 66.5 0.054 1 0.816 3 months PP Length -for-age -0.508 -0.890 69.0 0.184 1 0.660 Weight-for-age 0.322 -0.547 69.0 0.184 1 0.668 Weight-for- length -0.758 -0.000 66.5 0.096 1 0.757 6 months PP Length -for-age -1.049 -3.410 74.0 0.724 1 0.395 Weight-for-age -0.028 -1.177 76.0 0.905 1 0.341 Weight-for- length 1.038 0.413 77.5 1.054 1 0.305
Table 7.5. Results of Mann-Whitney U tests for growth differences in newborns/infants by those with mothers who worry about milk compared to those with mothers who do not worry about milk (BB = before birth, PP = post partum)
7.3 Social Relations 7.3.1 Marital communication/decision-making 7.3.1.1 Maternal: Two variables are significantly different for women who worry about marital communication/decision-making (n = 10) compared to those who do no worry about marital communication/decision-making (n = 33) (see Table 5.10): BMI and total amount of land owned. None of the other biodemographic variables are significantly different (Table 7.6)
157
Mann-Whitney Chi- No Yes U test square df p BMI 3 months BB 22.0 23.0 114.0 2.469 1 0.116 BMI 2 months BB 22.1 24.5 100.0 3.843 1 0.050 BMI 1 month BB 22.5 25.2 99 3.954 1 0.047 BMI 1 month PP 21.3 23.8 97.0 4.180 1 0.041 BMI 2 months PP 21.7 23.9 127 1.450 1 0.228 BMI 3 months PP 21.7 23.9 134 1.016 1 0.313 Summed skinfolds 52.2 69.5 109.5 2.546 1 0.111 Bioimpedence 29.5 33.6 118.5 1.791 1 0.181 MUAC 25.1 26.8 111.5 2.370 1 0.124 Calf circumference 31.1 32.4 122.5 1.494 1 0.222 weight change 3 months BB 2.26 3.73 49.0 0.219 1 0.640 weight change 1 month PP 1.37 0.69 21.0 0.187 1 0.665 Land owned 3.1 0.8 46.0 4.755 1 0.029 Land farmed 2.8 1.8 28.0 0.710 1 0.789
Table 7.6. Mann-Whitney U tests for difference in biosocial factors by mothers who worry about marital communication/decision-making compared to those who do not worry about marital communication/decision-making (shading indicates a statistically significant relationship).
7.3.1.2 Index Children: If mothers worried about marital communication/decision- making there were significant differences in z-scores for WAZ in the post partum period. WHZ at 6 months post partum was also significantly different for children of mothers who worry about marital communication/decision-making compared to children whose mothers did not worry about marital communication/decision-making (Table 7.7).
158
Mann-Whitney Chi- No Yes U test square df p 3 months BB Height-for-age -1.919 -1.30391.5 2.962 1 0.085 Weight-for-age -1.568 -0.86383.5 3.508 1 0.061 Weight-for-height -0.227 0.210 106.0 1.271 1 0.260 1 month PP Height-for-age -1.729 -1.315121.5 1.845 1 0.174 Weight-for-age 1.574 -0.911 92.0 4.774 1 0.029 Weight-for-height 0.463 0.101 108.5 2.968 1 0.085 3 months PP Height-for-age -1.412 -0.786107.5 2.733 1 0.098 Weight-for-age -1.394 -0.536 88.0 4.903 1 0.027 Weight-for-height -0.631 -0.005 112.0 2.322 1 0.128 6 months PP Height-for-age -1.264 -0.826112.0 1.704 1 0.192 Weight-for-age -1.434 -0.569 82.5 4.845 1 0.028 Weight-for-height -0.892 -0.071 86.0 4.387 1 0.036
Table 7.7. Results of Mann-Whitney U tests for mean differences in growth z-scores for index children by mother’s worry about marital communication/decision-making.
7.3.1.3 Newborn/Infant: Newborns and infants did not show differences in growth z- scores based on mothers worries about marital communication/decision-making. This does not follow the pattern seen among index children (Table 7.8).
159
Mann-Whitney Chi- No Yes U test square df p Birth Height -for-age -0.037 0.125 183.5 0.283 1 0.595 Weight-for-age -0.604 -0.747 190.5 0.538 1 0.463 Weight-for- height -0.466 -1.034 183.5 0.268 1 0.605 1 month PP Height-for-age -0.198 -0.547 195.5 0.510 1 0.475 Weight-for-age -0.040 -0.161 192.0 0.113 1 0.737 Weight-for- height -0.000 0.217 150.5 0.006 1 0.940 3 months PP Height-for-age -0.516 -0.596 184.0 0.298 1 0.585 Weight-for-age 0.153 0.618 136.0 0.685 1 0.404 Weight-for- height 0.557 1.196 99.5 3.546 1 0.060 6 months PP Height-for-age -1.201 -0.814 123.5 0.915 1 0.339 Weight-for-age -0.221 0.227 131.0 0.466 1 0.466 Weight-for- height 0.977 1.038 144.0 0.112 1 0.738
Table 7.8. Results of Mann-Whitney U tests for mean differences in growth z-scores for newborns/infants by mother’s worry about marital communication/decision-making.
7.3.2 Vurugu/fujo 7.3.2.1 Maternal: Biodemographic Associations: The only other nutritional marker that differs based on worries about vurugu/fujo is arm circumference change in the last trimester. No other nutritional markers differ between women who worry about vurugu/fujo as compared to those who do worry about vurugu/fujo in this sample. Total number of people listed on social networks differs with women who worry about vurugu/fujo; they have a smaller social network (Table 7.9).
160
Mann-Whitney Chi- No Yes U test square df p Age 24.8 24.8226.5 0.033 1 0.857 Parity 1.6 1.6 238.0 0.011 1 0.915 Gravidity 2.7 2.9 196.5 0.925 1 0.336 BMI 4 months BB 22.2 22.6 242.0 0.041 1 0.840 BMI 3 months BB 22.5 22.6 207.0 0.417 1 0.518 BMI 2 months BB 23.1 23.2 226.0 0.036 1 0.814 BMI 1 month BB 21.7 22.0 234.0 0.000 1 1.000 BMI 1 month PP 22.1 22.2 223.5 0.063 1 0.802 BMI 3 months PP 22.1 22.3 218.0 0.142 1 0.703 Summed skinfolds 58.0 53.2 243.0 0.293 1 0.588 Bioimpedence 31.1 29.5259.0 0.703 1 0.402 MUAC 25.4 25.6228 0.005 1 0.941 MUAC change last trimester -.705 0.57 78.0 4.729 1 0.030 MUAC change 1 to 3 months PP 1.22 0.60 259.0 2.121 1 0.134 Calf circumference 31.5 31.4 226.0 0.001 1 0.980 Rate weight change 3 months BB 2.8 2.2 76.0 0.379 1 0.538 Rate of weight change 1 month PP 1.4 1.1 24.0 0.004 1 0.949 Land owned 3.2 2.3 65.0 0.618 1 0.432 Land farmed 3.0 2.4 69.5 1.234 1 0.267 Birth space interval 27.7 32.0 200.0 0.659 1 0.417 Social support 21.8 18.2 143.5 1.922 1 0.166 Total names in support network 9.6 5.7 147.0 4.707 1 0.030
Table 7.9. Mann-Whitney U tests for difference in biosocial factors by mothers who worry about vurugu/fujo (n = 26) compared to those who do not worry about vurugu/fujo (n = 18).
In this sample of 18 women who worry about vurugu/fujo, five women reported experiencing domestic violence. Nutritional markers do not differ for women in domestic violence situations, but birth space interval is longer than that seen in women who do not have violent husbands. Support networks are much smaller for these five women which might indicate that they have much less social flexibility than others (Table 7.10).
161
Mann-Whitney Chi- No Yes U test square df p Age 25.2 23.4 121.0 0.582 1 0.445 Parity 1.6 1.8 82.0 0.527 1 0.468 Gravidity 2.8 3.0 83 0.431 1 0.511 BMI 3 months BB 22.5 22.2 94.0 0.047 1 0.828 BMI 1 month BB 23.3 22.2 123.0 0.690 1 0.406 BMI 1 month PP 22.4 20.5 114.0 0.256 1 0.613 BMI 3 months PP 22.4 20.4 140.0 2.087 1 0.149 Summed skinfolds 57.2 49.4 121.0 0.755 1 0.385 Bioimpedence 31.0 26.8 138.0 2.249 1 0.134 MUAC 25.6 25.1 114.5 0.396 1 0.529 MUAC change last trimester -0.3 0.6 33.0 2.271 1 0.132 MUAC change 1 to 3 months PP 1.1 0.05 106.0 1.979 1 0.159 Calf circumference 31.6 31.2 132.5 1.676 1 0.195 weight change 3 months BB 2.6 1.6 29.0 0.762 1 0.383 weight change 1 month PP 2.0 1.8 19.0 0.021 1 0.885 Land owned 2.9 1.25 15.0 0.689 1 0.407 Land farmed 2.2 0.25 19.0 2.247 1 0.134 Birth space interval 28.6 41.2 44.0 4.091 1 0.043 Social support 21.4 12.3 75.5 6.909 1 0.009 Total names on support network 8.8 2.3 75.5 5.033 1 0.025
Table 7.10. Results of Mann-Whitney U tests for differences in biosocial variables by worry about domestic violence (BB = before birth, PP = post partum; shading indicates statistical significance).
162 However, when these five women in domestic violence situations are assessed as individuals, a different pattern emerges which is not captured by these normative values but is reflected in the large standard deviations (Table 7.11).
Case Birth Space Contextual Information Interval 327 66.1 Husband is an alcoholic and very ill; she worries that cursing and witchcraft are responsible 446 34.1 Husband is an alcoholic 598 35.6 Widow, husband’s brother is now her husband, he is an alcoholic and extremely violent; situation taken to government authorities 629 20.0 She has epilepsy which is often associated with witchcraft and her husband is an alcoholic 943 50.4 She believes that her husband has been cursed and that witchcraft is involved because when her husband began sleeping outside the marriage he became violent toward her.
Table 7.11. Information on the individual lives of the five women in domestic violence situations.
Birth space intervals for these five women fall into two categories: short and long. Four women have birth space intervals longer than the sample mean; two women have an interval longer than 50 months, one is much shorter than the sample mean at 20.0 months (Table 7.10). Importantly, with sample sizes this small, the mean values in Table 7.13 do not capture the reality of the social situation as is described in above in Table 7.11. Although birth space interval is not a predictor of birth weight (see Table 4.29); other maternal anthropometric variables are associated with birth weights and anthropometric outcome measures in this sample; these results were presented in Chapter 4. To disaggregate violence from nutrition is not possible at this time therefore are treated separately although it is suspected that access to resources likely explains some motivations for violence. The effects of violence appear to be intergenerational. The table below shows the results of linear regression equations using violence to predict birth weight (Table 7.12).
163
Code Independent Variable F p R2/Adjusted R2 VIOTOTAL Fears of vurugu/fujo in general 7.587 0.009 0.153/0.133 VIOLENTHUS Domestic violence 9.241 0.004 0.177/0.158
Table 7.12. Results of linear regression equations for predicting birth weigh by violence category (shading indicates statistically significant).
7.3.2.2 Vurugu/fujo and Index Children: General vurugu/fujo, which is a worry for 18 women in this sample, does show an interesting relationship to the index child’s growth patterns. Using the CDC 2000 as a reference population; z-scores differ significantly for HAZ z-scores when the sample is categorized by mothers’ worry about vurugu/fujo. WAZ approaches significance on several measures but is does not differ significantly overall; nor do WHZ measures. These results are presented below for the months before birth and after the birth of a sibling (Table 7.13 and Table 7.14).
164 Vurugu /fujo N Mean Mann-Whitney U Test Chi-square df p 4 BB Height-for-age No 13 -1.525 94.0 3.235 1 .072 Yes 10 -2.093 Weight-for-age No 13 -1.411 79.0 0.189 1 .664 Yes 10 -1.639 Weight-for-height No 13 -.339 46.0 1.388 1 .239 Yes 10 0.10 3 BB Height-for-age No 23 -1.431 267.0 5.617 1 .018 Yes 16 -2.179 Weight-for-age No 23 -1.018 233.0 3.265 1 .071 Yes 16 -1.844 Weight-for-height No 23 0.054 197.5 0.558 1 .455
165 Yes 16 -.283 2 BB Height-for-age No 24 -1.263 334.0 9.004 1 .003 Yes 18 -2.161 Weight-for-age No 24 -1.068 310.0 3.929 1 .07 Yes 18 -1.934 Weight-for-height No 24 -0.133 241.5 0.420 1 .517 Yes 18 -0.464 1 BB Height-for-age No 26 -1.278 331.0 5.362 1 .021 Yes 18 -2.057 Weight-for-age No 26 -1.042 310.5 3.335 1 .068 Yes 18 -1.900 Weight-for-height No 26 -0.178 276.5 1.029 1 .31 Yes 18 -0.539
Table 7.13. Comparing z-score means (CDC 2000) by vurugu/fujo categories before birth (BB = before birth).
Vurugu/ fujo N Mean Mann-Whitney U Test Chi-square df p Birth Height-for-age No 21 -1.082 238 4.605 1 .032 Yes 16 -1.876 Weight-for-age No 21 -1.040 187.5 0.357 1 0.55 Yes 16 -1.602 Weight-for-height No 21 -0.397 153.0 0.212 1 .646 Yes 16 -0.363 1 PP Height-for-age No 26 -1.133 314.0 3.647 1 .056 Yes 18 -1.877 Weight-for-age No 26 -1.011 290.5 1.820 1 .177 Yes 18 -1.877 Weight-for-height No 26 -0.309 256.5 0-.289 1 .591 164 Yes 18 -0.458 2 PP Height-for-age No 26 -1.204 Yes 18 -1.657 279.5 1.180 1 .227 Weight-for-age No 26 -1.031 Yes 18 -1.609 272.5 0.845 1 .358 Weight-for-height No 26 -0.295 Yes 18 -0.624 252.5 0.195 1 .659 3 PP Height-for-age No 26 -1.031 320.0 4.216 1 .040 Yes 18 -1.609 Weight-for-age No 26 -0.855 284.5 1.454 1 .228 Yes 18 -1.586 Weight-for-height No 26 -0.285 255.5 0.263 1 .608 Yes 18 -0.691
Table 7.14 Comparing z-scores means (CDC 2000) for index children in the months after birth by vurugu/fujo category (PP = post partum) (Continued). 166 Table 7.17. Continued.
Vurugu/ fujo N Mean Mann-Whitney U Test Chi-square df p 4 PP Height-for-age No 26 -.898 314.0 3.647 1 .056 Yes 18 -1.494 Weight-for-age No 26 -0.903 219.5 1.884 1 .170 Yes 18 -1.494 Weight-for-height No 26 -0.463 265.0 0.548 1 .459 Yes 18 -0.829
165
167 7.3.2.3 Vurugu/fujo and Newborns/Infants: A similar pattern exists for the newborns as well. Although z-scores are not different in LAZ (except at 4 months of age), scores for WAZ and WLZ are significantly different at many measures. These results are presented below (Table 7.15).
168 Vurugu/ fujo N Mean Mann-Whitney U Test Chi-square df p Birth Height-for-age No 25 0.059 264 0.924 1 .337 Yes 18 -0.48 Weight-for-age No 25 -.0362 339.0 7.882 1 .005 Yes 18 -0.960 Weight-for-height No 25 -0.224 294.5 2.928 1 .087 Yes 18 -1.080 1 PP Height-for-age No 26 0.015 318.0 4.021 1 .045 Yes 18 -0.661 Weight-for-age No 26 0.347 377.5 11.738 1 .001 Yes 18 -0.584 Weight-for-height No 26 0.315 264.0 1.141 1 .285 Yes 18 -0.584 169 2 PP Height-for-age No 26 -0.181 280 3.478 1 .062 Yes 16 -0.729 Weight-for-age No 26 0.711 352.5 10.672 1 .001 Yes 16 -0.353 Weight-for-height No 26 0.885 274.0 2.922 1 .087 Yes 16 0.119 3 PP Height-for-age No 26 -0.352 314.0 3.647 1 .056 Yes 18 -0.802 Weight-for-age No 26 0.728 363.5 9.558 1 .002 Yes 18 -0.351 Weight-for-height No 26 1.094 345.0 7.022 1 .008 Yes 18 0.218
Table 7.15. Comparing z-score means (CDC 2000) for newborns/infants by worry about vurugu/fujo (Continued)
Table 7.15 continued.
Vurugu/ fujo N Mean Mann-Whitney U Test Chi-square df p 4 PP Height-for-age No 26 -0.462 314.5 4.199 1 0.04 Yes 17 -0.986 Weight-for-age No 26 0.499 330.0 5.869 1 .015 Yes 17 -0.503 Weight-for-height No 26 1.015 305.0 3.312 1 .069 Yes 17 -0.249 5 PP Height-for-age No 26 -0.709 310.0 2.558 1 .110 Yes 17 -1.108 Weight-for-age No 26 0.433 348.5 7.473 1 .006 Yes 17 -0.645 Weight-for-height No 26 1.238 327.4 4.982 1 .026
170 Yes 17 0.293 6 PP Height-for-age No 25 -1.040 238.0 0.427 1 .513 Yes 17 -1.192 Weight-for-age No 25 0.341 314.0 6.767 1 .009 Yes 17 -0.747 Weight-for-height No 25 1.472 309.5 6.179 1 .013 Yes 17 0.312 7 PP Height-for-age No 10 -0.963 64.0 .823 1 .364 Yes 10 -1.427 Weight-for-age No 10 -0.026 67.5 1.753 1 .186 Yes 10 -0.992 Weight-for-height No 10 1.049 13.5 3.158 1 .076 Yes 10 0.292
170 Although the differences in HAZ scores are not significantly different (except at 4 months after birth). The pattern is similar to that seen in the index children suggesting that this category of vurugu/fujo might actually represent women who are in a more vulnerable position in society than those who do not identify vurugu/fujo as a worry. Vurugu/fujo has interesting implications for the fetus/newborn and the index child. Both categorical variables of vurugu/fujo and a woman’s employment status predicted the birth weight of the newborn in regression analysis but the interaction of the two was not significant. Birth weight was treated as the dependent variable and vurugu/fujo and mother’s employment categorized in two different ways. Women who did not worry about vurugu/fujo had babies that, on average, weighed 300 grams more than babies born to women who did worry about vurugu/fujo (3.266 kg vs. 2.952 kg). This difference was also significant for women who worked for money (coded as 3); birth weights differed by about 660 grams. The same difference was significant for women who brewed beer (coded as 4) and worried about vurugu/fujo; the birth weight of their newborns was approximately 700 grams less than those born to women who did not worry about vurugu/fujo but did brew beer (3.523 vs. 2.830 kg.) (Table 7.16).
Mann- Vurugu/fujo Vurugu/fujo Whitney Chi- Category N – no N - yes U test square df p Work for 4 3.530 6 2.870 24.0 6.545 1 .011 Money Brew Beer 3 3.523 3 2.830 9.0 3.857 A 0.05
Table 7.16. A comparison of birth weights from women who work for money or brew beer and their worries of vurugu/fujo.
In most cases, the brewing of beer was done by women who could not rely on their husbands; they need a way to generate an income for household survival. Vurugu/fujo, may capture the women who have less access to resources, less reliable social networks, those more likely to suffer in a famine year. This could perhaps explain why their
171 children’s growth was compromised compared to those who do not worry about vurugu/fujo. A comparison of the growth standard results of index children and newborns indicates that a long-term consequence of this vurugu/fujo categorization may be compromised stature that begins in utero. It may be that for mothers expressing a worry about vurugu/fujo actually reflects both on their lifetime and current vulnerabilities or feelings of uncertainty. These results also suggest that perhaps this worry about vurugu/fujo (or vulnerability), actually might be used to identify “at-risk pregnancies and children” because it may identify the segment of the population with the least access to resources, least dependable social network, and those more vulnerable to nutritional stress. In other words, this may capture women’s feelings about their ability to buffer their children in this relatively unpredictable environment. Women who identified their husbands as “unemployed” due to illness, laziness, or drinking had the highest anxiety and depression scores on the HSCL-25. This association is not surprising; a pregnant mother who is totally responsible for the household survival will be worried about her own well being, the well being of her children, and the outcome of her pregnancy. She will not easily be able to work after the birth of a newborn and does not have a secure network of people if she can not rely on her husband in times of need. Women with working husbands (i.e., men who own a business or work for others) have slightly higher depression and anxiety scores than farmers. One explanation is that women have higher workloads when their husbands are away from the home on a daily basis. This is probably true for women living outside of the town. But for women living close to or in the town center, this is not the case. Most of these mothers do not farm and usually do not have animals to maintain; women referred to themselves housewives with primary responsibility being child care, cooking, laundry, and household maintenance. Most of these women were the ones who voiced concerns about the lack of an independent means to sustain themselves or that they rely heavily on their husbands (especially for everyday things like soap or clothing). Even though many of these women were in the higher wealth category, wealth did not translate into lower anxiety and depression scores for this group of women.
172 Employment status of women also reflects some of the ideological changes that occurred as the Iraqw out-migrated from the homeland. Seven out of seven women who are able to generate their own income (through the market, by sewing, or working for others (kibarua) do not live in virilocal residences. The two women who make money selling in the market can not rely on their father-in-law in times of need. Only two of the seven women working independently to raise money can rely on their father-in-law. The two women who could work as tailors averaged more than seven years of education and so did their husbands. Seventy-eight percent of those women who primarily farm live in virilocal residences and 33% of these women can rely on their father-in-law in times of need. Half of the women identifying themselves as housewives live in virilocal residences and 43% of them can rely on their father-in-law. Some of this partitioning can be explained by women’s worries about vurugu/fujo. I initially expected inquiries about vurugu/fujo to elicit responses about the prevalence of drinking and the bar culture (klabu) which is a relatively recent phenomenon in the area. While this is a worry for women, in general, most women did not worry about drinking unless it affected their lives directly. For example, beer brewing is one way that women can make money. There are seven women in this sample of 46 that brewed beer at some point in the project (three brewed regularly); four of these women said they could not rely on their husbands in times of need and only one said that her father-in-law was reliable in times of need. Patterns of growth curves are poorer for both index children and newborns from violent households (n = 5). Index children from the domestic violence households tend to fall about 1 standard deviation below the rest of the sample for HAZ. They fall nearly 2 standard deviations below the reference population mean. Following these patterns, WHZ z-scores are approximately 1 standard deviation below that of children whose mother does not worry about domestic violence (Figures 7.1 – 7.3)
173 Height-for-Age for Index Children
0
-1
-2
174 -3
Z-Score 2000) (CDC -4 -4-3-2-1B1234567 Monthly Measure (B = birth of sibling)
No Domestic Violence Domestic Violence
Figure 7.1. Height-for-age z-scores for index children comparing those not in violent household to those in violent households.
Weight-for-Age for Index Children
0
2000) -1
-2
175 -3
Z-Score (CDC -4 -4-3-2-1B1234567 Monthly Measure (B = birth of sibling)
No Domestic Violence Domestic Violence
Figure 7.2. Weight-for-age z-scores for index children comparing those not in violent household to those in violent households.
175
Weight-for-Height for Index Children
0.5 0 -0.5 -1 -1.5 -2 176 -2.5
Z-Score 2000) (CDC -3 -4 -3 -2 -1 B 1 2 3 4 5 6 7 Monthly Measure (B = birth of sibling)
No Domestic Violence Domestic Violence
Figure 7.3. Weight-for-height z-scores for index children comparing those not in violent household to those in violent households. 176 Newborns are also below the sample and reference populations means the duration of the study. At birth newborns from violent households are born approximately ½ a standard deviation below sample and reference population means in height-for-weight z-scores. For WAZ z-scores, newborns/infants tend to stay approximately 1 standard deviation below the sample mean. However, for WLZ z-scores newborns are equal in the first 28 days of life. Thereafter, newborns from violent households fell to approximately 1 ½ a standard deviation below the rest of the sample of infants (Figure 7.4 – 7.6).
177
Length-for-Age for Newborns/Infants
1 0 -1
178 -2 -3
Z-Score 2000) (CDC -4 B1234567 Monthly Measure (B = birth)
No Domestic Violence Domestic Violence
Figure 7.4. Length-for-age z-scores for newborns comparing those not in violent household to those in violent households.
Weight-for-Age for Newborns/Infants
1 0 -1
179 -2 -3
Z-Score (CDC 2000) -4 B1234567 Monthly Measure (B = birth)
No Domestic Violence Domestic Violence
Figure 7.5. Weight-for-age z-scores for newborns comparing those not in violent household to those in violent households.
179
Weight-for-Length for Newborn/Infant
1.5 1 0.5
180 0 -0.5
Z-Score (CDC 2000) -1 B1234567 Monthly Measure (B = birth)
No Domestic Violence Domestic Violence
Figure 7.6. Weight-for-age z-scores for newborns comparing those not in violent household to those in violent households.
180 CHAPTER 8
DISCUSSION
5.1 Introduction In this dissertation I have examined aspects of young Iraqw women’s lives from biomedical and ethnographic perspectives. I preface this discussion with three quotes from anthropologist, Ole Bjorn Rekdal: In the eyes of outsiders, African societies have often been inextricably bound up to static qualities that this stasis has become a defining characteristic. If they change, according to this view, they simply cease to exist. A major contributor to Iraqw ethnography has recently been recorded to lament that “Iraqw culture” does not exist any more, blaming the nationalist policies of Julius Nyerere for this sad outcome (1996: 5-6).
And, he states that
Commodisation, westernisation, and modernisation have often been depicted as inevitable and universal processes that will eventually lead to the cultural homogenisation of the peoples of the world (1996: 7-8).
181 And last,
The idea of a static and passive culture which reacts to external influences by falling apart or disappearing, or by becoming corrupt, malformed or homogenised does not fit well with the ethnography of the Iraqw. No do I think that other cultures in Africa fall in this pattern. Not only do external forces have impact on these societies; they also provoke responses, whose characteristics may help explain why the homogenisation prophecies of modernisation theory have not yet materialized. In Marshall D. Sahlin’s words, “[t]he very ways societies change have their own authenticity, so that global modernity is often reproduced as local diversity (Sahlins 1994: 377). The flexibility of Iraqw “custom” and the inventions by Iraqw tradition represent such authentic processes… a continually changing authentic Iraqw culture (1996:23).
Part of the reason that these quotes are influential to my thinking is that I have been able to assess the strengths and limitations inherent in my own research focusing on social change as a mediator of health and well being. I focus on the context of the lives of 45 women; and generalizations to the larger population are limited but the details of their lives are evidence for “cultural continuity and successful adaptation to a rapidly changing environment” (Rekdal 1996: 45). In health studies, sweeping population level generalizations (epidemiological approaches) are incredibly informative and provide information on risk categories for morbidity and mortality. However, these approaches fail to capture the intricacies of every day life which is where the negotiation of larger more remote influences, such as economics, interface with the community and individual. In addition, “resilience” seems undervalued in the biomedical approach (cf. Engle et al. 1996; Kent 1991; Scheper-Hughs and Sargent 1998). Understanding of local context and ecologies may provide insight into protective mechanisms occurring at this level that can be promoted in community health programs. 8.2 Historical Context I have begun to understand how a young Iraqw woman negotiates all the demands of those dependent on her on a daily basis. Given what I have read and observed about Iraqw lifeways, I support assessments of recent researchers who state that life for the Iraqw has become more complex through education, Christianity, increased mobility, relaxed interpretations of Iraqw moral ideology, and national/international economics and 182 politics (Maddox et al. 1996; Snyder 1993; Rekdal 1996), but also recognize that change is inevitable in all societies and not necessarily “abnormal”. These documented historical changes are embraced in the “traditional” Iraqw system of peace and harmony while at the same time notions of modernization rebuke such tradition; perhaps this is why the Iraqw are concurrently generalized as “traditional” and “progressive” (Snyder 1993; Rekdal 1996). I focused on young women because most of these women were born at a time when primary education was free and compulsory; the majority of women (35/46) in this study had 7 years of primary education which is more than any previous generation of women in this area of northern Tanzania. It is this generation of young women who are most likely the ones constructing the newest strategies of survival which are a blend of strategies from “traditional” perspectives, altered by historical contingency, and taking place in the present. They attended school; they were introduced to new ideologies about progress, nationalism, and capitalism, and did not have the same opportunity for “home education” during those schooling hours. This observation has been corroborated by their parents and grandparents; they say that the young women (and men) lost some opportunity for “culture education” because they were not at home throughout much of the day to learn how their mothers (fathers) negotiated their days and that formal schooling and Christianity created a dichotomy between traditional and modern. Interestingly, for most Iraqw women, education itself has not changed a woman’s role in society (Buchert 1994; Lewinson 2000; Snyder n.d.); but it probably has delayed age of marriage which might explain, among other reasons, why these married Iraqw women “feel” less fertile than previous generations. Post-primary education is probably the most influential variable affecting women’s empowerment; in this part of Tanzania post-primary education is rare (Omari and Mbilinyi 2000). In colonial Tanzania, primary education promoted women’s roles as caretakers and acted as a ““delocalized” institution for cultural transmission” (Kilbride and Kilbride 1990: 86). In the 1980s, Tanzanian social equality rhetoric was promoted, although the academic curriculum did not change much (Omari and Mbilinyi 2000). Those women with opportunity for higher education were directed into home economics; and most became teachers, nurses, or midwives
183 (Buchert 1994; Lewinson 2000; Rogers 1983). The remaining majority of women will go to school for seven years or less, get married, and have children. I am not suggesting that primary education is useless; nor am I suggesting that the younger generation does not understand cultural ideology. I believe they have a different understanding of life than that of their parents which has been influenced by this formal education and through notions of modernization. Although all Iraqw are contending with these same issues, I chose to work with these young women to understand how the details of their lives may complicate or enhance their ability to function under these circumstances given the expectations of high fertility and the need to provide their own children with more education, the need for accessing the market economy, and the desire to pull away from elder’s authority. At the same time women must contend with less social power and more economic difficulty than most men. Two characteristics of the population are intriguing given the current political- economic circumstances; the first is demographic – fertility rates remain quite high at 7.4 (Olsen 2000) and it appears that mortality (although too high) is not as high as that seen in other parts of Africa (Olsen 2000). The second is migration – the Iraqw continue to move into new geographical and ecological settings. Given the unpredictability of the environment and the presence of localized famines; these two characteristics underscore the resilience of Iraqw peoples. I was fortunate enough to work in the Haydom area when there was no famine (2001 -2). Thus, this research is about young women’s daily negotiations during a “good year”. Questions remain as to how negotiations would change in a famine year. From a human biology perspective, it is assumed that culture is a source of variability and a human adaptive mechanism allowing human populations to adjust to changes in the local environment – environment defined most broadly (Harrison 1993; Frisancho 1993; , 1995 1982; Armelagos et al. 1992). The physical and cultural environment in the Arusha and Manyara regions has changed dramatically in the last century. The Iraqw began out-migrating from a small homeland area where they practiced intensive agriculture techniques and raised cattle (Illife 1979; Raikes 1975). The out-migration began slowly at first, picked up speed again, was halted by testse flies
184 and cattle raids, and then, in the last 70 years has picked up speed, with the Iraqw now the dominant population in at least four districts. The out-migration parallels changes in modes of production. It was during this time that the Iraqw began prioritizing maize rather than millet and sorghums (Iliffe 1979). The building of Haydom Lutheran Hospital in the 1950s created a minimal infrastructure in this remote area of Tanganyika through the construction of roads and bridges; the town of Haydom is adjacent to the hospital (Figure 8.1).
Figure 8.1. Arial view of Haydom Hospital during the rainy season (picture by Dr. Olsen).
The hospital pays employees and creates a relatively stable market economy in the town of Haydom as hospital workers are paid in cash. The consistent money supply means that people can buy goods and potentially save capital. Many workers are also shop owners or have relatives that own shops/restaurants/hotels in the vicinity. Others moved into the Haydom catchment to be closer to the hospital for a variety of health
185 reasons, while others moved there in hopes of finding a way to access the monetized economy through employment. In the last decade, Tanzania has shifted from a socialist country to a multi-party democracy. Tanzania, although always an economically peripheral country, is suffering from the effects of structural adjustment. These large scale political-economic changes are reflected in some health measures (Kent 1991). Since the governmental shift in 1995, infant and child mortality rates have increased. More Tanzanian children died in 1999 than in 1996. Infant mortality rates dropped from 91.6 to 87.5 per 1000 live births between 1991 and 1996. However, in 1999 this number rose to 99.0 per 1000 live births. Under age five mortality rates follow a similar pattern. Between 1992 and 1996, under five mortality rates dropped from 140.9 to 136.5. In 1999, this number increased to 146 under five deaths per 1000 live births (Tanzanian Bureau of Statistics 1997; 2000). By the end of the 1990s, Tanzanian children were suffering worse than they had in the beginning of the 1990s. The large-scale national changes have permeated into the thinking of rural Tanzanians as well. There is a strong desire to be a part of the market economy. Many women state that the lack of capital and the ability to save money is one of their biggest concerns. In the context of this research it is expected that the rapid political-economic changes and increasing mortality experienced by Tanzanians may translate into effects for sub-populations as well, including the Iraqw. How do such changes infiltrate ideology of reproduction and gender roles? A discussion centered on the three original questions asked in chapter 1 is presented below given the context of social change just described. 8.3 Birth Transition, Developmental Niche and Health Outcomes 8.3.1 Will there be a change in anthropometric measures, especially in the rates of weight and height change by the index child before and after the birth of a sibling?
The data indicate that the birth of a sibling, treated as an impetus for social role change for the triad, may be a slight risk factor for negative patterns of growth or increased likelihood for illness in the first 3 months post partum for some children. A description of the cultural context of the birth transition suggests that mothers worry about the index child in the immediate post partum because of food sharing. It seems 186 that mothers assess the well being of all of their children in this transition. If a mother believes any one of her children is less healthy than the others she will consciously make an effort share her post partum food specifically with that child. Children are assessed by their overall “fatness” and there appear to be differences in maternal perception or expectation by sex. Fatness is often associated with health. Snyder recorded these words in prayers recited at the elders’ council meeting (2001:130):
Let our women and girls agree in their discussions Let our young men listen to the words of their elders Among ourselves, let us agree in our discussions Let our leaders have good health and grow fat And agree with our words and advice
When compared to the reference population boys are shorter and lighter for their age than girls. However within this sample boys and girls are essentially the same weight and height at any given age (see Figures). If girls and boys are the same size at any given age, how does a mother decide who to feed or not to feed extra food? Are there examples of gender-biased buffering? Among the Iraqw, the ideal family is one in which a grandchild is born for each grandparent; therefore, there is a strong desire for both boys and girls, at least two of each sex. In this sample, most women were having their second child so I do not suspect that bias would occur at this point in family development as a result of the desire for male children. There was one instance in which a woman had a second girl and her husband was distraught and did not want to help in the post partum period; he did not sleep at the home for several months after the birth of the newborn. In another case, a woman had her third girl and her husband is quoted as saying ‘it is not a problem, I love all my children’. There does appear to be different patterns in caretaking for boys and girls. For example, the number of minutes an index child spent crying and the number of comforting episodes were different for boys and girls. While the mother was pregnant boys cried for an average of 11.1 minutes in the observation periods whereas girls cried
187 less, an average of 9.0 minutes. After birth, both boys and girls cried less but again boys cried more than the girls. The average number of minutes spent crying by boys was 9.8 minutes whereas girls cried for an average of 6.2 minutes in observation periods post partum. In general girls seem to cry less than boys. Comforting episodes show a similar trend. During the mother’s pregnancy, both boys and girls are comforted approximately 2.2 times in each observation period; however, in the post partum period both are comforted less often, but boys are comforted more often than girls (1.5 vs. 1.1, respectively). This may reflect that until a new is born, boys are more dependent; whereas girls are groomed to be more independent and self-comforting throughout early childhood. The instilling of gender ideology in children needs further investigation, especially as it pertains to diet, activity, and parental expectations of development and responsibility. Another interesting pattern shows up in activity. Before the birth of a sibling, boys, on average, spend 26.2% of their time out of the mother’s sight. Girls, on average, spend 18.3% of their time out of the mother’s sight. In the post partum period, there is a shift in the amount of time spent out of the mother’s sight. The boys spend slightly more time in mother’s sight; there is a slight drop from 26.2% to 23.7%. Girls place of activity changes dramatically. There is a significant increase in the amount of time spent out of the mother’s sight; an increase from 18.3% to 35.5%. In general, boys spend a little less time away from their mothers and girls spend a much larger percentage of time away from their mothers in the post partum period. This may explain why all boys have an increased rate of weight gain; in general the boys’ socioemotional responses to the newborn were associated with reduced activity. One explanation is that fathers tend to stay at home in the post partum period (in the post partum period fathers were present 58.8% of visits whereas before birth they were present only 36.8% of visits). Perhaps, this indirectly increases the amount of time a young boy stays at home. If they are less active during this time and spend time closer to both of their parents; they may have better access to foods, exert less energy, and eat a little more than usual. Girls seem to become more active and spend more time away from their mothers in the post partum period. In general, girls were more often playing with friends and
188 relatives outside of the house in the post partum period. They may have increased activity levels. Perhaps only the girls who the mother is worrying about will gain more weight through her conscious choice of food sharing. These observations are interesting because when a male child is born it is announced that a “child of the bush” is born implying that he is “free to roam outside of the household” (Snyder 1997:565) and a girl is announced as a child who “will fetch water” implying a tie to the household. In the post partum, boys spend less time “in the bush” and girls spend less time inside of the home and more time playing with peers and interacting with others. There are no differences for either boys or girls in average distance to mother when in her presence. The number of crying episodes, duration of crying episodes, comforting episodes, or percentage of time spent out of mother’s sight when dichotomized by adjustment category is not significantly different. Overall, the trend may be best explained by the fact that boys in general tend to have lower WHZ and WAZ scores than girls and mothers will tend to buffer boys during the transition. Girls are groomed to be more independent than boys in early childhood and during the transition become less needy of mother’s attention and will access other caretakers readily. In sum, boys tend to be lighter for their age and for their height compared to girls; mothers may perceive boys as more vulnerable than girls and may buffer all boys for this reason. Girls may only be buffered if the mother notices weight changes. This observation could be explained by activity patterns changes; more activity and less direct contact with mother may lead them gain less weight in the early post partum months.
8.3.2 Are changes in body composition of the mother reflected in the newborn and/or index child throughout the birth transition?
It appears that maternal buffering is transient and has immediate effects in the first few months post partum but does not carry out beyond six months post partum. These results indicate that the birth transition is a period of buffering for all members of the household. A negative impact of increasing parity may have its greatest impact when mothers’ daily routines become more normalized; approximately four to six months after birth. A larger percentage of newborns and index children were sick at the end of the
189 study (or in the 6th and 7th months post partum). For the infant, this coincides with the time they need more nutrients than can be provided by breast milk and a period of increased exploration of their environment (Wiley and Pike 1998; Zeitlyn 1995). Over the course of the birth transition, diet breadth will decrease gradually as post partum foods fall out of the diet, women’s work increases, and breastfeeding declines due to supplementation and changes in activity. Perhaps it is this time in which children become most vulnerable rather than in the first few months. 8.3.3 Is maternal social status assessed by her social network, psychosocial stress levels, autonomy and household composition, associated with outcome variables for any of the three members of the triad?
Iraqw discuss intergenerational ideological conflicts that affect land distribution, social relations, and adherence to traditional values. Many Iraqw families still practice ultimogeniture (i.e., the youngest son inherits the parents land and home) and live in virilocal residences. A growing number of Iraqw couples, including the youngest male live away from their parents and maintain independent households. Most of these households rely more on money as a medium of exchange and are likely to be town dwellers or live in the immediate outskirts of Haydom town (i.e., within a 15 – 20 minute walk of the town center). This ideological and geographical divide does not capture the idiosyncrasies of everyday life that influence the well being of the triad. The psychosocial stress survey employed in this research shows interesting trends that reflect on social networks and shifts in the economic sector. It is interesting that women who identify their husband’s job as primarily farming have the lowest anxiety and depression scores on the HSCL-25. Women whose husbands work for money have slightly higher scores and women whose husbands do not contribute to the household have the highest scores. The first and last associations are relatively easy to explain. As one of the first food-producing societies in East Africa, farming has always been an important part of Iraqw lifeways even with the change from millet and sorghums to maize, beans, and pumpkins. For at least three generations, Iraqw have been growing maize and beans (among other crops) and have experienced a few major famines with localized famines as the norm. Social networks have shifted to accommodate the 190 geographic expansion and new farming techniques. Iraqw rely on members of their family living in different eco-zones because planting and harvesting timing varies slightly and it is unlikely that everyone will experience famine in the same year (Snyder 1993). The shift in farming techniques coincided with missionary work and notions of modernity. As tradition is disregarded under certain circumstances, women are less restricted by cosmology concerning the neetlaamee (or male spirits) and are able to travel long distances. Women are regularly seen on buses or walking to visit relatives in distant villages. While at the same time that women have increased mobility which allows them to access their social network more readily, notions of self-interest have become detrimental to social relations. In the past, to deny an individual of some basic need is said to have been against Iraqw moral ideology (Snyder 1993; Rekdal 1996). Today, the elders complain that it is difficult to find individuals to donate livestock for ceremonies performed for community well being (Snyder 1997). In the past, community cleansing rituals were important for “community social, economic and political life” (Snyder 1997: 573), and individuals would not refuse to participate or donate a goat or sheep for fear of causing disharmony in the community. “‘Today people don’t care, they will only agree if you give them cash’” (Snyder 1997: 568). The same is true for post partum care; historically a neighbor would not refuse to give a family a sheep or goat to slaughter after the birth of a newborn; today, however, people are not likely to even ask their neighbors. It is the responsibility of the couple and their families to find/buy appropriate post partum foods. If a woman’s husband does not prepare for this, the woman will independently make arrangements before birth in order to insure she has appropriate types of foods to regain her strength after the birth. There was one incident of mortality in this sample of 46 triads. A male child, under the age of five, died from malaria when his newborn sibling was less than a year old. Was this partially driven by the mothers’ inability to divide her time and energy among three children? Under what circumstances could this death have been avoided? The mother reported that she did not have enough money to take the child to the hospital. She asked her deceased husband’s brother (her current husband) and his relatives for help
191 and they refused. She could not go to her family because she could not travel while the child was sick. When the husband’s family realized that the situation was life threatening, they complied. However, it was too late and the child died quickly upon arriving at the hospital 8.4 Theoretical Implications 8.4.1 Parent-Offspring Conflict: The results of this research partially support Trivers’ hypothesis of parent-offspring conflict. There appears to be no dramatic health compromises associated with weaning and the presence of a newborn sibling among the Iraqw of Tanzania. Although many children expressed negativity toward the mother and the newborn, these behaviors did not translate into poor health or growth outcomes over the course of the transition for the group although it certainly held true for some individuals. Bateson (1994) has suggested that “evolutionary arguments need to be looked at again not simply from the standpoint of honest signaling but also baring in mind how an individual’s state might affect the optima” (1994: 399). Bateson points out that relationships are dynamic, and individuals will need to continuously appraise one another such that mothers will be “sensitive to the condition of the its offspring” and young should be “sensitive to the condition of their mother and adjust their pattern of development accordingly” (1994: 401). This means that reproductive effort is constantly shifting and is momentarily dependent. From the mother’s perspective she should be able to decide based on honest assessments of and honest signals from her offspring whether steady or increasing parental care for the current offspring will be more beneficial than investing in future offspring. The same is true from the offspring’s perspective; the offspring must also be sensitive to the mother’s state and pick up on information from the mother about how to develop. Nutritional buffering in the post partum period not only benefits the mother but also the children she focuses on. The newborn directly benefits from the breast milk and low activity levels of the mother. The index child may or may not be buffered depending on mothers’ assessments of the child in the first month post partum. The influential aspects of the dynamics of the maternal-child interactions are difficult to define. In this sample of mothers, many chose to continue breastfeeding into
192 the pregnancy. Perhaps, they chose to continue investing in the index child through breastfeeding because it was a “good year” (i.e., no famine). Most women were not nutritionally stressed and did not feel that continuing to breastfeed was a threat to the developing fetus. Based on birth weights, this assumption holds true because there were only 2 infants were born below the 2500 gram risk category; interestingly, neither of these mothers were breastfeeding at conception. Contrary to parent-offspring conflict theory, index children who responded negatively to the presence of the newborn were not more likely suffer from illness nor were their growth measures compromised in comparison to children who did not express negative behavior toward the mother or the newborn. It was apparent that mothers were assessing the well being of the index children but that this assessment was not about the child’s behavior in relation to the newborn. Mothers consciously chose to give their food to the child(ren) they thought needed it most, which may be some evidence for the dynamics involved in the simultaneous management of raising multiple dependent offspring. 8.4.2 Future Directions: The results of this study of the birth transition introduce many questions for future research. First, despite the threat of localized famine and the impact of the larger political-economic situation, mothers and children appear to be quite healthy. Part of this can be explained by the management of social networks and the retention of ideological beliefs surrounding the birth of a child. Post partum care and feeding practices among the Iraqw appear to benefit not only the mother and the nursing newborn but also other children in the home. Future research would benefit from detailed analysis of diet breadth and micronutrient assessments because anemia is so prevalent and interacts with immunocompetence. 8.4.2.1 Vurugu/fujo: Although most families are able to thrive in this unpredictable and economically changing environment, the effects of uncertainty are likely linked to or are mediating variables for understanding Iraqw views about vurugu/fujo. Local understandings and experiences with vurugu/fujo were explored in this research. Evaluating a woman’s psychosocial well being needs further investigation because attempts to analyze the burden and emotional toll of uncertainty and social exclusion are rare (cf. Kleinman and Cohen 2001; Pike 2004) and this study shows that worries of
193 uncertainty are associated with pregnancy outcomes and growth of children. Iraqw women are responsible for the well being and survival of their children; worries about uncertainty in provisioning for them may be reflected in their psychosocial scores. Worries about hunger serve as powerful expression of shame among Chagga peoples of Mount Kilimanjaro (Howard and Millard 1994); perhaps idioms expressing uncertainty among the Iraqw are similar to Chagga worries of hunger. The use of a well tested questionnaire may be predictive of women who are at risk for poor pregnancy outcome when used in conjunction with idioms of distress and worries about uncertainty. It appears that asking women about vurugu/fujo actually captures women whose past and/or current situation is less than ideal. Indeed, the questionnaire used in this research needs further refinement. 8.4.2.2 Domestic Violence: There is no doubt that “violence against women has consequences for their physical as well as mental health” (Asling-Monemi 2003:10). Among the five women in this sample whose husband’s were violent, HSCL-25 scores go up and the growth status of their children declines. The United Nations began investigating domestic violence as a ‘hidden problem’ in the early 1990s (United Nations 1993; Davies 1997) and the WHO only recently prioritized domestic violence as a health issue (1997). Domestic violence in the developing country setting is increasing as a public concern and little data has been reported from around the globe in the last 25 years (Bradley 1997; Koenig et al. 2003). Although the sample includes only five women; this means that approximately 10% of women in this sample were battered or threatened by their husband’s physical violence. These numbers are low when compared to other large-scale surveys conducted in developing countries. In Uganda, 30% of women (n = 5109) reported experiencing physical threats and abuse (Koenig et al. 2003). Mary Ellsberg conducted the “first population-based epidemiological research on domestic violence and mental health” in Nicaragua in 1993 (1999:31). She reports that over 50% of ever-married women of childbearing age experienced violence at least once in their lifetime and of those women 27% reported an episode within the last year (1999). Violent acts included kicks,
194 punches, beating up, blows with an object, and threats or use of a weapon; 70% of reported episodes were one or more of these types listed for the Nicaraguan women. Documenting the consequences of domestic violence is critical; there are also consequences for children. One study from Costa Rica shows that newborns weighed nearly a ½ kg less if their mothers were battered during pregnancy (Nunez-Rivas et al. 2003). These battered mothers were also three times as likely to have a newborn weighing less than 2500g which puts them at greater risk for morbidity and mortality (Kramer 1987; Nunez-Rivas et al. 2003). There is mounting evidence to suggest that infant and child mortality increases among households with mothers that experience physical violence (Asling-Monemi et al. 2003). This holds true in the present study as well. Research in Nicaragua shows that violence in the reproductive years is associated with increased risk for infant and child mortality. Preterm delivery and low birth weight were the main causes of death among neonates; and children were six times as likely to die before age five if their mother was abused (Asling-Monemi 2003). These data indicate that chronic stress experienced by the mother is not only reflected in her HSCL- 25 scores but shows that the suffering is intergenerational. There is no assumption that violence itself is a direct cause of increased mortality or poorer growth but rather that it is a factor for identifying segments of the population at greater risk for poor outcome and increased risk for mortality. The data from this research also support conclusions from large-scale cross- sectional surveys which show that social isolation is associated with domestic violence. Women are more isolated when they are victims of domestic violence but there is also data to suggest that isolation is also causal (Dobash and Dobash 1979, Gelles 1974; Heise 1998; Nielsen et al. 1992). Of the five women who admitted that their husband was violent, three were interviewed about their social network. When asked to free list the people they could rely on, the average number of people for these three women was 2.3. Women in non-violent homes listed an average of 8.8 people. When asked how many people on their list they see daily, the average for these three women was less than one (0.33) whereas the average for the rest of the sample was 2.9. Although domestic
195 violence may be common, it is not a topic of conversation among women. In focus groups, women would not openly discuss their own experiences, but when asked if they knew anyone who had been abused, more than half of the women said they did know at least one person. Heise (1998) offers a framework for cross-cultural research on domestic violence. based on Belsky’s ecological approach to child abuse and neglect (1980). The framework assumes that there are “embedded levels of causality” (Heise 1998: 264). Heise identifies fours levels of analysis: I. macrosystem, II. exosystem, III. microsystem, and IV. ontogenic. To begin to understand domestic violence in rural Tanzania, the questions proposed by Heise in the ecological framework are addressed below: I. Attitudes/Norms: 1. Is masculinity defined in terms of honor, dominance, or aggression? 2. Does culture tolerate interpersonal violence? 3. Are women considered inferior or the property of men?
II. Alcohol/Poverty/Isolation 4. What is the level of alcohol abuse in the community 5. What is the level of economic stress (unemployment) 6. .What is the level of exogamy?
III. Male dominance/Communication 7. Do men control the wealth in the family 8. Do men control decision-making in the family 9. Is communication between the couples common?
IV. Level of physical abuse among children 10. Did husband experience/witness violence as a child
8.4.3 Attitudes/Norms: In general the Iraqw would not be categorized as an aggressive population. Individuals prefer not to have to become physically violent to defend their honor. For example, I present a bit of ethnographic material to show some of attitudes/norms of Iraqw peoples towards violence against children. Iraqw women typically march to protest about community problems such as alcoholism or abuse in primary schools (Snyder 1997, 1999, n.d). In the course of this fieldwork, I was present for one of these marches. One male primary school teacher had been drinking alcohol and became physically violent with several of the children (one had to be hospitalized). 196 Women left their homes and slept outside “in the bush” and refused to return home until a proper and just punishment was given to this teacher. They debated for several days with individual men and women taking turns speaking. Women, who normally do not carry a walking stick (fimbo) would hold the man’s stick while speaking in front of the crowd, and men while speaking would not hold the fimbo, but rather would hold a leaf instead. Men and women, by these acts were metaphorically and realistically shifting power. The women’s protest was their way of expressing their control over community morality; men were expected to come up with an acceptable solution to the problems presented by this group of mothers. If their decisions were not acceptable, the women would continue to sleep “in the bush” until an acceptable resolution was presented by the men. The abbreviated example shows that physical abuse does occur among the Iraqw. It also shows that women, as mothers, feel obligated to protect their children and will go to extremes to have their voices heard by men and protect their children. It shows that their resolution process is democratic and peaceful, which is how the Iraqw would describe themselves (Snyder 1993; 2002). 8.4.4 Alcohol/Poverty/Isolation/Male Dominance/Decision-making: Based on focus group interviews and other ethnographic literature, alcoholism is becoming more of a problem in this area of Tanzania and probably can not be disassociated from poverty (Snyder 1997, 1999). Financial security is a problem for most families. Many men and women worried that they would not be able to afford medical bills if hospitalization were needed or higher education for their children. Taxes are problematic. First, the taxes are relatively high; and second, the local government is known to be corrupt and many individuals reported that the village office would take your last animal if you could not pay your taxes. Economic stress and lack of access to the market economy are major worries in this community. The Iraqw are patrilineal; inheritance is from fathers to sons (Snyder 1997). Generally, couples will live in close proximity to the husband’s family but it is becoming more common for couples to relocate. However, this relocation does not sever social network ties. Snyder points out that the uterine kin are equally important among the Iraqw (Snyder 1993, n.d.). Several women in this sample owned their own small
197 livestock, chickens, kitchen items, and in a few cases some land. However, these are exceptions rather than the rule, most women do not own land or livestock but this does not exclude them from decision making. Many women in this sample said that she and her husband plan decisions together. There is quite a range of variation in decision- making and marital communication/decision-making. As a generalization, men have the most control over household decisions and resources but this generalization must be considered in light of the colonial history because “the imposition of a foreign political, economic, and administrative structure resulted in a re-formulation of the public sphere” such that “This failure to recognize the work and role of women or to provide them educational or economic opportunities resulted in women being relegated to a domestic sphere that had, in the pre-colonial had more seamlessly merged into the public arena” (Snyder 2000, n.d: 15). 8.4.3 Child Abuse: I have no way to assess levels of child abuse on a community level. Over the course of the year I would hear about occurrences like the one described above concerning child abuse in the primary school. Another field worker from Norway was conducting research on this topic and she reported being surprised by the levels of abuse of children interviewed at the public schools. Given this ecological framework, a question remains: why did these five men abuse their wives? Four out of five of these men were described by their wives as alcoholics. Drinking oversimplifies the answer. Social marginalization of Iraqw men as a result of their colonial experience has recently been described by Snyder (n.d.). Men’s social marginalization impacts women directly and indirectly through men’s devaluation in the public sphere which increases women’s burdens in the household (Snyder n.d.). Women identify themselves as mothers and it is the mother who is morally superior to all others in society (Snyder 1993). Women protect their children and will act on their behalf because their roles as mothers are so highly valued. However, there were no marches protesting marital abuse. 8.5 Summary The birth of a sibling is a normal transition for most children. Some older siblings reacted negatively to the presence of a newborn which is likely in response to changes in
198 interactions with the mother. There were significant differences in time spent away from the mother by gender after the birth of a sibling. In the post partum, girls were able to spend time away from the mother probably because they have been groomed for greater independence as compared to boys in early childhood. One male child reacted extremely to this situation and his health measures, behaviors, and interactions with caretakers reflected on his negative behavior toward the mother and the newborn. This child took the longest of the 45 children to get used to being an older sibling. His weight loss, severe illness, foolish behavior, and interactions with caretakers were extreme and not likely the norm in any population, but rather an example of the extreme end of the continuum. Proximity to mother did not change when in her sight. Most children stayed very near to the mother in the post partum period when they were with her. The reallocation of maternal investment that was expected with the birth of a sibling is more complex than parent-child interactions captures. In the immediate post partum, there are often other caretakers intervening and taking care of the needs of the mother and her other children. However, women were conscious of the well being of all of their children and would buffer them from nutritional stress by sharing their post partum foods. Strong support for genetic conflict between mothers and offspring is not provided based on negative behaviors observed as part of weaning and the transition to an older sibling (Trivers 1974). There is moderate support for child regression to earlier stage of development but mothers did not seem to give extra care when the child acted “foolishly”; it mostly elicited chiding remarks from caretakers. All children, regardless of age, were expected to become a “big child” with the birth of a new sibling. Girls especially matured quickly after the birth of the sibling. In this sample there were six girls who were very young (< 22 months) when their sibling was born, only one out of these six children had difficulties adjusting to the presence of the newborn. Although the others would occasionally react “foolishly” toward the newborn or mother, most of the time their maturity levels in the post partum were surprising to the researcher. There were no boys in the study who were less than 22 months of age at the birth of their sibling. Based on Trivers’ ideas I expected these children to have the most difficult time adjusting because they were so young. This was not supported; there was no predicting
199 which children would react poorly (from a behavioral perspective) to the newborn, and which would be welcoming. Most often, girls adjusted more readily than boys to the presence of a newborn. This may reflect on gender ideology; boys although free to roam around and spend time away from the household, seem to be more attached to their mothers than girls. Boys’ rate of weight gain in the first three months after birth either reflects a gender bias in assessments of health by mothers or reflects activity changes occurring with the presence of a newborn sibling. The dynamics of these relationships are difficult to ascertain. Bateson’s (1994) perspective on relationships emphasizes that children and parents must provide honest cues to one another about their needs. Both mothers and index children brought about changes in the post partum period. Girls, for example, stayed out of the house more. Mothers, for example, made conscious choices about feeding their children. It is plausible that the triad is buffered by family members and through ideology of post partum care. The birth transition may not affect health in the first few months, but may actually have its greatest impact when post partum help and post partum foods are withdrawn. Probably sometime after 4 months post partum, post partum foods will fall from the diet, a mother will return to her duties, and she will become fully responsible for the household again. Perhaps it is at this time that the effects of raising multiple dependent children will have its greatest impact on her health and the health of her dependents. Future research should include collecting data on the timing of mortality after the birth of a sibling to see if there is a vulnerable period that occurs within the first 6 – 12 months after the birth of a sibling as compared to the first six months after birth. Among the Iraqw, early childhood is primarily mediated through interactions with the mother. At the birth of a sibling, there is a shift in mediating variables. The dynamics of relations among the triad over the birth transition are mediated by the mother’s psychosocial well being and social network. A focus on women in violent households shows that the health and well being of her fetus/newborn and her other children are compromised in comparison to children from non-violent homes. The social networks of these women are definitely not as complex as those seen among other sub- groups of women in this sample.
200 In sum, lactation, weaning, pregnancy and birth are not isolated physiological events in a woman’s reproductive span. As with all aspects of reproduction, these events do not occur in a vacuum, but rather as part of a social context. While pregnant, a woman has to carefully balance her needs with those of the fetus and her living dependents. In evolutionary terms, the hope is that the probability of risk will be minimized for oneself and each offspring while maintaining future reproductive potential. Stress, while independently related to reproductive outcomes, also acts as a mediator for the other selective mechanisms mentioned in this research. Lack of outlets for frustration, unpredictability in intensity and duration of a stressor and indications of worsening conditions can limit one’s ability to cope. One goal of research focused on psychosocial stress as a mediator of health, should be about coping and one’s ability to thrive in current circumstances. We need to document who it is that thrives and why it that they can thrive given challenging circumstances. Patterns of resilience in difficult circumstances can be compared across populations. Part of the success of such an approach is that individuals will be treated as active participants in their world and not simply be reduced to biological systems. Future research should combine the concept of adaptability with more subjective notions of distress and coping to understand the range of flexibility in defining reproductive success in a specific ecological setting. Weaning and pregnancy are complex life history events that influence and are influenced by the pregnant woman. Pregnancy is a time when a woman becomes the environment for another individual and this biological change alters the environments of others dependent on her. Indeed reproduction takes place in a unique environment which includes larger more remote geographical influences as well as more direct and local influences. Human flexibility is part of this environment, and likely a critical part of that environment. What is lacking in demographically or epidemiologically oriented projects is the microdemographic quality data that actually contextualizes health outcomes in a holist manner (Berman et al. 1994). To conclude, this initial study focusing on biosocial perspectives on reproduction among the Iraqw of Tanzania has raised many questions. There is no straightforward finding that the birth of a sibling creates a vulnerable period of time for the index child.
201 However, the protective behaviors noted indicate that mothers (and newborns) are nutritionally buffered during this time and that mothers do nutritionally buffer some children under certain circumstances. There is ample evidence to suggest that social networks are critical to health and well being and that shifts in gender ideology in this younger generation may confound negative effects. Future research will focus on the details of social networks and the effects of shifting gender ideology in the context of reproduction and child caretaking. A quick overview the major findings from this research follows: Biodemographically: 1. Mean age at birth of a sibling is 29.9 months and mean age at weaning is 20.5 months.
2. If children are weaned before 21 months they have lower z-scores compared to the those with longer birth intervals.
3. 71% of the women in this sample were breastfeeding at conception
4. Female index children were breastfed an average of 1.5 months into pregnancy and males 2.8 months
5. If there was no overlap in lactation and pregnancy the index child was older (37.1 months).
6. The help of mother-in-law is associated with shorter birth intervals and earlier weaning
7. Supplementation is strongly correlated with work schedules.
Psychosocial: 1. Anxiety and depression scores differ for women by employment status. Farming is associated with the lowest scores and working for money associated with the highest scores.
2. Distance from town center is associated with the type of residence and employment status.
3. Birth weights also differ by employment status
4. Anxiety and depression scores differ by husbands’ employment status
202 5. Women’s worries are associated with different scores on the HSCL – 25; social support networks often reflect worries as well, especially worries about vurugu/fujo (the unknown) and domestic violence
Anthropometric: 1. Maternal nutritional status probably explains 10% of variance in birth weight
2. Birth weights are associated with worries the mother identified (cattle).
3. Household help is associated with better z-scores for newborns right at supplementation time and when the child begins to become more mobile
4. Newborns peak at 6 months for weight-for-length z-scores
5. If mother identifies cattle as a worry, her children have lower height-for-age and weight-for-age z-scores.
6. Some index children gain weight faster in the post partum period and it may be due to maternal buffering.
7. Girls the mother identifies as “still adjusting” to the newborn gain weight at a faster rate in the postpartum.
8.6 Applications The design of this research project was unique in that it was intended to capture some variables of interest to epidemiologists and international health communities without compromising context. The sample size was large enough to make some generalizations to the larger population, while maintaining an understanding the lives of women on a daily basis. Part of the reason for this approach is that epidemiology and public health have come quite far; for example child mortality rates have dropped dramatically over the last 70 years in most countries. However, there is a paradox that remains a challenge in anthropology and international health circles -- 11 million children will die from preventable deaths every year (UNICEF 2001:68). I believe that detailed biocultural studies will allow researchers to begin to address this paradox and why there is variation between and within sub-populations, especially in environments peripheral to the national economy, with limited access to education, a poor nutritional base, and high rates of morbidity and mortality. The main conclusions can be summarized as follows:
203 1. Life style incongruity (the process of producing an authentic Iraqw culture in the new political economic arena) has an impact on mental and physical health. • Women living closer to the town center have higher depression and anxiety scores and wealthier women did not have lower scores. It appears that living in a town means that women are more isolated from their relatives and have reduced physical activity; birth space intervals reflect this.
• Women in Harar and Getanyamba (i.e., living further from town, have lower anxiety and depression scores and their birth intervals seem to be dependent on the accessibility of the social network on a daily basis.
• From a public health perspective it appears that household helpers reduce the responsibility burdens of a mother; and their children benefit. However, if young uneducated women are the household helpers; advocating this approach may be counter-productive. Investigations into who is helping women in their homes needs attention.
2. The benefits of the post partum recuperative period should be promoted locally. The hospital has made and is making great strides in teaching. For example, women will now eat eggs while pregnant. They have abandoned this “traditional” belief easily. Women pointed out to me that the post partum recuperative period is becoming shorter than in the past. Perhaps emphasis on its benefits for maternal and child health may help to retain this beneficial aspect of Iraqw reproductive ideology.
3. Focus groups and education for men and women on the negative impact of violence for both mothers and children may have its greatest impact if pitched in the context of fertility and its threat to harmony.
4. The emotional burden of vulnerability, unpredictability, or lack of control has created pockets of vulnerable people (both men and women). At this time, among these young women, the most vulnerable appear to be those women who can not rely on their husband’s family. Reliance on in-laws in general, mother-in-law, and father-in-law are associated with poorer outcomes.
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Zeitlin MF, Ahmed NU, Zeitlin JA, Super CM, and Guldan GS. 1995. Developmental, behavioral, and environmental risk factors for diarrhoea among rural Bangladeshi children of less than two years. Journal of Diarrhoeal Disease Research 13:99-105.
231 APPENDIX A
RESEARCH CLEARANCE AND TANZANIAN SUPPORT OF RESEARCH
232 233
234
235
236 237 APPENDIX B
IRB
238 239 APPENDIX C
EXAMPLES OF SURVEY QUESTIONS
240 Basic Information: 1. Name(s) – (first, second, third) 2. Husband’s Name(s) 3. Kitogoji, Kijiji/Balozi 4. Tlahhay 5. Da’awi 6. Birthdate 7. Age 8. Birthplace (month/day/year) or season if known 9. Older brothers, Younger brothers 10. Older sisters, Younger sisters 11. Parents alive? 12. Where do they live now? 13. Is this where you grew up? a. If no, where did you grow up? 14. How many years of schooling 15. How many years of schooling did your husband have? 16. Age at first menses 17. Age at first pregnancy 18. Are you currently experiencing any unusual illnesses? 19. Children Name sex birthdate age m/sb/d/a place of delivery Breastfeed – how long 20. Does anyone else live in your household? Name sex age relation reason job/occupation 21. How many animals are owned by this household? a. cows b. goats c. sheep d. chickens e. donkeys f. pigs 22. Is the household currently lending anyone animals? Name relation animal type how many how long/return when 23. Are you between 4 ½ and 7 months pregnant? 24. Do you have 1, 2, or 3 children born to you? 25. Are you older than 20 but younger than 30? 26. When was your LMP? 27. When do you expect this child to be born (early/mid/end of month __)? 28. This child will be your _____ child. 29. Are you still breatfeeding your youngest child? a. When did you wean this child (month/year) b. How old was the child? c. Did this cause difficulty? In what way? 30. How many times have you moved since you were married? 31. Where will you deliver? 32. What month/year were you married? 33. Throughout the year will you ever live somewhere else? 34. How do you describe the temperament of your children?
241 35. Are you and your children relatively healthy people or are you sickly? 36. Are any of your children living with someone else? a. who relation how long reason 37. Have you ever had a miscarriage? a. how many? b. how many months pregnant were you? 38. Have you ever given birth to a child that only survived a few hours or days? 39. Husband’s age 40. You are which wife? first wife/cowife, second wife/cowife, third wife/cowife 41. Is you husband alive? Did he die? Circumstances? 42. This husband is your # husband?
242 Family Environment: 1. This month has anyone left/come into your household? a. total number of visitors b. who c. relationship (gender) 2. A. If you need money, what will you do? a. why b. when c. how often B. When is the last time, you needed money? 3. Do you always share money with other members of your extended family a. how b. when c. how much d. reason 4. How much land to you own (you and your husband)? 5. A. How much land do you rent B. How much land do you rent out to others? a. who b. relation c. how much d. how long 6. How much of this land do you farm? 7. What kind of farm equipment do you own? 8. Do you rent any or rent out any farm equipment? 9. Have ______(you, your children, your husband) slept anywhere else this month? a. where b. reason 10. When you are not watching your child, who is? a. jina b. uhusiano c. jinsi d. umri gani e. masaa mangapi 11. How many hours are you in direct contact with your child/ren? 12. How many hours is your child with another caretaker? 13. Do you rent land to anyone else a. who b. relation c. how much d. for how long 14. A. Do you have problems with your husband’s family? B. Do you have problems with your family? 15. Do you work outside the home?
243 Health 1. What types of illness have you had this month (vomiting, cold, cough, eye infection, malaria/fever, skin rash, accidents, nausea, earache, headache, heartache, measles, convulsion, swelling of glands, chiggers, curse by person, cursed by spirits) a. type b. how long c. mild or severe d. treatment e. did this illness follow an unusual event (marital conflict, wedding, etc.) f. what did you do the few days before getting sick? 2. What types of illness have your child/children had this month a. type b. how long c. mild or severe d. treatment e. did this illness ¾ first child ¾ second child ¾ third child 3. Do you feel healthy now/today? 4. Are your children healthy now/today? 5. How many days were you sick this month? 6. How many days was index child sick this month? 7. How many days was your first/second/third child sick this month? 8. Injuries/accidents this month? 9. Do you smoke? a. for how long? 10. Does your husband smoke a. what kind and for how long
244 Psychosocial 1. Has index child slept anywhere else this month? a. when (date) – for how long? b. s/he stayed with whom? 2. Has your first/second/third child stayed somewhere else this month? 3. Have you experienced any stressful events (marital conflict, alcohol, loss of animals, poor crops) a. type b. time of day c. scale 1-5 (1 = mild, 5 = severe) d. how long did it last (minutes, days, weeks) e. who, in the household, was most affected f. how did you respond (sleep, cry, not eat, leave the house) 4. Has your child/children experienced any stressful events? a. type b. time of day c. scale 1-5 (1 = mild, 5 = severe) d. how long did it last (minutes, days, weeks) e. who, in the household, was most affected f. how did you respond (sleep, cry, not eat, leave the house) 5. Does you child have trouble eating? a. how often b. doe sthis occur regularly c. what is the duration of the problem d. are problems with food always the same e. how do you feel when the child has eating problems 6. Does your child have trouble sleeping? a. how often b. does this occur regularly c. what is the duration of the problem (seconds, minutes, days, weeks, always) d. are problems with sleep always the same e. how do you react when the child has sleeping problems 7. Have you had any marital conflicts this month a. Describe b. How would you rank the conflict 1-5 8. How do you characterize the temperament of ______child? a. Index, first, second, third 9. Where do the children sleep (bed, foam mattress, floor, with you)? 10. How do you characterize your marriage? 11. How do you characterize the temperament of your husband? 12. Do you have marital conflict? 13. Does your child act like this everyday or is today different? 14. Is there anything that has made your child especially ______this month? a. Furaha b. upset c. scared d. worried e. angry f. excited
245 15. What would make your life and that of your children easier right now? 16. A. How many children do you have outside of this marriage? a. gender b. age c. live where B. How many children does your husband have outside this marriage? a. gender b. age c. live where 17. Does this child(ren) live with you or your parents? 18. Does your husband have other women outside of marriage/does he visit other women? a. what is the result of this? 19. If your husband left for a long time, who would you ask for help? a. what would you do? 20. What is your worst problem right now?
246 Social Support: 1. A. Excluding us, how many visitors have you had this week? (who, when, how long, what reason, what did you give them) B. This month? 2. A. Who have you visited this week B. This month? 3. A. If you need money, what will you do? B. If you need money, who do you ask first, second, third, etc. 4. A. If you need help with your work, what will you do? B. If you need help with your work, who do you ask first, second, third, etc. 5. Do you exchange work with another person (who, gender, relation, when, for how long, for what reason) 6. Do you exchange childcare with another person (who, gender, relation, when, for how long, for what reason) 7. Do you ask someone else to help you with childcare? 8. Who do you talk to about important matters (first, second, third, etc.)? 9. A. If you need food, what will you do? B. If you need food, who do you ask for help (first, second, third, etc.)? 10. If you need help with childcare, what will you do, who will watch the child? 11. Does anyone come to talk to you about important matters? 12. Does anyone ask you for help with money, food, or work? (who, relation, reason, for how long/how much, etc.) 13. Who do turn to to talk about your problems? 14. How many neighbors do you have? 15. Do you own things separate from your husband? 16. If you could talk to anyone about your problems, who would you like to talk to? About what? 17. Do you want to talk to your family about your problems? 18. Who gives you good advice (about what)?
247 Autonomy: 1. Can you sell a chicken without asking someone? 2. Can you sell maize without asking someone? 3. Can you sell beans without asking someone? 4. Can you buy chicken without asking someone? 5. Maize? 6. Beans? 7. Can you travel without asking someone? 8. Can you help someone without asking someone? 9. Can you go to greet your parents without permission? 10. If your child is sick, can you take your child to the hospital without asking someone? 11. Are you able to go to a seminar or meeting without asking?
248 APPENDIX D
SWAHILI VERSION OF HOPKINS SYMPTOM CHECKLIST-25
249 1 = hamna hata kidogo (not at all), 2 = kidogo ( a little), 3 = ipo kiasi (some), 4 = ipo sana (extremely), 8 = sijui (I don’t know)
Question in English Code Swahli 1. To feel suddenly afraid without reason RQ1 1. Kuwa na woga ghafla bila sababu 2. To be afraid RQ2 2. Kuwa na woga woga 3. To feel like you will faint, dizziness, or RQ3 3. Kuwa na hali ya kutaka kuzirai, lose strength kuzunguzungu au kukosa nguvu 4. To feel anxious RQ4 4. Kuwa na wasiwasi 5. For your heart to beat much faster than RQ5 5. Moyo kudunda sana kuliko usual kawaida 6. To tremble or shake RQ6 6. Mwili kutetemeka 7. To feel tightness in the body because of RQ7 7. Kutokuwa na utulivu anxiety or be without calmness 8. To have headache RQ8 8. Kuumaua kichwa au kujisikia kuumaw na kichwa 9. To have periods of fear or great worry RQ9 9. Kuwa na hofu au hali ya hofu 10. To be so worried that you can’t sit RQ10 10. Kujisikia hali ya kuhangaika quietly any place hadi huwezi kukaa mahali umetulia 11. To lose strength and feel that you do RQ11 11. Kukosa ngumu au kukosa you do you daily activities slowly nguvua na kufanya shughuli za kila siku polepole 12. To blame yourself for things which RQ12 12. Kujilaumu kwa matukio have happened to you or to others yanayotokea na yanakuhusua wewe 13. To cry easily RQ13 13. Kulia bila sababu 14. To not have sexual appetite or to be RQ14 14. Kutokuwa na hamu ya uninterested in sexual activities kujamiiana 15. to lose appetite for food RQ15 15. Kukosa hamu ya kula chakula 16. When you go to bed you fail to fall RQ16 16. Wakati unapolala unashindwa asleep or sleep all night until morning kupata usingizi au kulala moja kwa moja 17. Your discouraged about the future RQ17 17. Kukata tamaa kaitka siku za usoni/mebeleni, kukata tamaa katika sikku za usoni/mbeleni 18. You are not happy RQ18 18. Kukosa raha 19. To feel lonely RQ19 19. Kuwa mpweke 20. To have thoughts of taking your own RQ20 20. Kuwa na mawazo ya life kuyachukua maisha yako (sumu au kijnyonga) 21. To feel like you have no way out of RQ21 21. Kujiona hakuna njia ya kujitoa your troubles katika mataizo uliyonayo 22. To have many troubling thoughts RQ22 22. Kuna na mawazo mengi
250 23. To have no desire for anything – RQ23 23. Kukosa hamu ya vitu ambayo things which are important to life ni muhimu 24. To feel like you can’t do anything RQ24 24. Kujilazimisha kwenye shuguli except if you feel obligated zako au kujilazimisha kukosa umuhimu wakuishi katika nafasi yako? 25. To feel like you have no importance or RQ25 25. Kukosa umuhimu wa nafsi reason for living yako
251 APPENDIX E
CODES FOR STATISTICAL ANALYSIS
252 Variable VARIABLE LABEL Categories Identification ID Member of triad TRI 1 – mother 2 – index child 3 – newborn Live in multiple family units MFU 0 – no 1 – yes Live in same home with in-laws LIVEINLAWS 0 – no 1 – yes Monthly Measure MEASURE - 7 – 7 Gestation estimation GESTATION Before birth or postpartum BBPP 0 – before birth 1 – postpartum Age AGE Height/length in centimeters HTCM Space between live births in months BIRTHSPACE Birth weight, kg. BIRTHWEIGHT Lower and upper 10% in birth weight distribution BSU10PERCENT 0 = not in upper/lower 10% 1 = in upper/lower 10% Birth space category for upper/lower 10% in BIRTHSPACEUC 0 = between 18 – 47 months months 1 = less than 18 or greater than 47 months Sex of previous child PRESAMESEX 0 – no 1 – yes Presence or absence of illness MORBIDCAT 0 – no 1 – yes Presence or absence of illness in postpartum MORBIDCATPP 0 – no 1 – yes Total days of illness MORBIDDAYD Morbidity by monthly measure MDBB6 – MD7 Change in lengths, cm HTCHANGECM Rate of change in height HTCHRATE Monthly change in height calculated by rate HTCALCBYRATE Height in month of measure HTCMBB7 – HTCMPP7 Gestation before 38 weeks B438WEEKS 0 – no 1 – yes Weight-for-height z-score (CDC 2000) CDCWT4HTZ Weight-for-height of sample z-score WT4HTZSAMP Height-for-age z-score (CDC 2000) CDCHT4AGEZ Height-for-age of sample z-score TH4AGESAMPZ Weight-for-age z-score (CDC 2000) CDCWT4AGEZ Weight-for-age of sample z-score WT4AGESAMPZ Months of lactation into the pregnancy MOLACT Trimester lactated into TRILACTATE Lactational status TL01 0 – no 1 – yes Lactate in first or second trimester TL12 0 – no 1 – yes Lactate in second or third trimester TL23 0 – no 1 – yes Lactate in third trimester TL03 0 – no 1 – yes 253 Help in postpartum HELPERS 0 – no 1 – yes Newborn’s date of birth DOBNB Month of newborn’s birth MONTHBIRTH Age category of index child at birth of sibling AGEBIRTHCAT 0 - <21 months 1 - >21 months Sex of index/newborn SEX 0 – male 1 – female Employment category of mother EMPLOYCATMOM 1 – home 2 – farm 3 – work for money Employment category of mother MOMEMPLOBEER 1 – home 2 – farm 3 – work for money 4 – brew beer Can you relay on your husband in general? RELYHUSGEN 0 – no 1 – yes Can your children walk to their in-laws without WALKINLAWS 0 – no you? 1 – yes Does your mother-in-law help you? MOMLAWHELP 0 – no 1 – yes In which month postpartum did you return to doing RETURNWORK most of your chores? In which month postpartum did you begin to SUPPLFEED supplement the newborn’s diet? Monthly measuring category MEASCAT What is the index child’s birth order? FAMPOS What is the season of this measurement SEAMEAS How many months did index child breastfeed? WEAN Categories of weaning by months WEANCATEGORY 1 – less or equal to 18 months 2 – between 18 and 24 months 3 – greater than 24 months Categories of weaning WEANRANK 0 – less or equal to 18 months 1 – greater than 18 months Mother’s lactational status at conceptions LACTSTATCAT 0 – not lactating 1 – lactating Birthspacing categories BSCAT 1 = less than 18 months 2 = between 18 – 24 months
3 = 24+ months Birthspacing categories BSCATEGORY 0 – less than 21 months 1 – greater than 21 months Birthspacing categories BSCATECORY01 0 – less than 18 months 1 – greater than 18 months Is your child used to the newborn? ADJUST 0 – adjusted 1 – still adjusting 254 Age categories for mother and index child AGECAT Index 1 – less than 18 months 2 – 18 - 24 months 3 – 24 + months Mother 1 – less than 24 2 – 24 – 29 3 – 29+ Husband’s employment status HUSEMPLO Farm Money None Husband’s employment status HUSEMPLOYCAT 0 – none 1 - employed Did your previous pregnancy result in a live birth? PREVBSLIVE 0 – no 1 – yes Did you previous pregnancy end poorly? PREVSBNOTLIV 0 – no 1 – yes Category of previous reproductive event PREVREPEVENT 0 – poor 1 – live Did you have marital problems while pregnant? MARITALPROBBB 0 – no 1 – yes Did you have marital problems since birth MARITALPROBPP 0 – no 1 – yes Is there a male child from this marriage? MALECHILD 0 – no 1 – yes Was there a male child from this marriage before MALEBB 0 – no this birth? 1 – yes Are the index and newborn the same sex? SAMESEX 0 – no 1 – yes How many live births have you had? PARITY How many pregnancies have you had? GRAVIDITY What is your wife number? WIFENO What is your marital status? MARSTATUS 1 – first marriage for both wife and husband 2 – second plus marriage for husband 3 – married but a widow How many months have you been married? MONTHSMARRIE What is your husband’s age? HUSGAE Wealth category based on house type and things WEALTHCAT 1 – very poor owned 2 – average poor 3 – wealthier Number of buildings on property BUILDNO Category by building number BUILDCAT 1 – 1 building 2 – 2+ buildings What is your child’s character normally? TEMPERAMENT 1 – happy 2 – quiet and shy 3 – happy and loud 4 – outgoing 5 – clever Temperament categories TEMPERCATS 1 – happy, loud, clever 2 – quiet and shy 255 3 - outgoing Temperament categories TEMPERCATS2 1 – happy, loud, outgoing, clever 2 – shy and quiet Housing type HOUSETYPE 1 – mud and thatch 2 – mud and flat 3 – brick and/or tin roof In which month did you conceive? MONTHCONCPT Name of village VILL Number of days between measures DAYBTMEAS Weight in kg KILOS Change in kg between measures KILOCHANGE Monthly weight measures BBK7 – PPK7 Change in weight in months 1 – 3 postpartum KILOCHANGE 13 Body Mass Index (wt, kg/ ht (m2) BMI Sum of four skinfolds SUMSKIN Body fat percentage BIOIMPED Mid-upper arm circumference, cm MUAC Calf circumference, cm CALFCIRC Head circumference, cm HEADCIRC Category of muac change MUACCAT 0 - <0 cm 1 - >0 cm Calculated weight for height WTFORHT Presence of illness MORBID 0 – no 1 – yes Presence of diarrhea DIAHHREA 0 – no 1 – yes Presence of eye infection EYEINFECT 0 – no 1 – yes Presence of flu FLU 0 – no 1 – yes Presence of cold COLD 0 – no 1 – yes Presence of malaria MALARIA 0 – no 1 – yes Presence of fever FEVER 0 – no 1 – yes Presence of other health problems OTHER 0 – no 1 – yes Presence of skin infection SKININFECT 0 – no 1 – yes Presence of cough/pneumonia COUGHPNEU 0 – no 1 – yes Presence of ear infections EARINFECT 0 – no 1 – yes Date measurement was taken DATEMEASURE Height squared HTSQ Rate of weight change RATEKILO z-score for BMI (CDC 2000) BMIZ Head circumference z-score (CDC 2000) HCIRCUMZ Number of siblings mother has MOMSIBS Number of older brothers mother has MOMOB Number of younger brothers mother has MOMYB Number of older sisters mother has MOMOS Number of younger sisters mother has MOMYS 256 Number of siblings of husband HUSSIBS Number of older brothers of husband HUSOB Number of younger brothers of husband HUSYB Number of older sisters of husband HUSOS Number of younger sisters of husband HUSYS Is your mother alive? MOMSMOS 0 – no 1 – yes Is your father alive MOMSDAD 0 – no 1 – yes Years of education of mother MOMEDU Years of education of her husband HUSEDU Total amount of land owned by couple LANDOWN Total amount of land farmed this year LANDFARM Age at menarche AGEMENARCH Age at first pregnancy AGE1PREGO Does anyone else live in your home? LIVEWITH 0 – no 1 – yes How many cows do you own? COWS How many goats do you own? GOATS How many sheep do you own? SHEEP How many donkeys do you own? DONKEYS How many pigs do you own? PIGS How many cows are on loan? COWLOAN How many goats are on loan? GOATLOAN How many sheep are on loan? SHEEPLOAN How many donkeys are on loan? DONKEYLOAN How many pigs are on loan? PIGLOAN Can you sell a chicken without asking someone? I1 0 – no 1 - yes Can you sell maize without asking someone? I2 0 – no 1 - yes Can you sell beans without asking someone? I3 0 – no 1 - yes Can you buy chicken without asking someone? I4 0 – no 1 - yes Maize? I5 0 – no 1 - yes Beans? I6 0 – no 1 - yes Can you travel without asking someone? I7 0 – no 1 - yes Can you help someone without asking someone? I8 0 – no 1 - yes Can you go to greet your parents without I9 0 – no permission? 1 - yes If your child is sick, can you take your child to the I10 0 – no hospital without asking someone? 1 - yes Are you able to go to a seminar or meeting without I11 0 – no permission? 1 - yes Do you visit family/friends enough? SS1 0 – no not at all 0 – not enough 1 – fair amount 257 2 – ok 3 - enough rank household help SS2 0 – none 1 – not enough 2 – mediocre 3 – enough rank ability for money in emergencies SS3 0 – none 1 – not enough 2 – mediocre 3 – enough rank if you are complemented for motherhood SS4 0 – none skills 1 – not enough 2 – mediocre 3 – enough rank your perception of others concern for you SS5 0 – none 1 – not enough 2 – mediocre 3 – enough rank the level of love in your household SS6 0 – none 1 – not enough 2 – mediocre 3 – enough rank whether you talk to someone about your work SS7 0 – none duties 1 – not enough 2 – mediocre 3 – enough rank your opportunity to discuss household SS8 0 – none problems with others 1 – not enough 2 – mediocre 3 – enough Do you talk with others about matters of money? SS9 0 – none 1 – not enough 2 – mediocre 3 – enough Do others visit you? SS10 0 – none 1 – not enough 2 – mediocre 3 – enough Do you receive advice? SS11 0 – none 1 – not enough 2 – mediocre 3 – enough If you should need to travel far do you have help SS12 0 – none available to allow this? 1 – not enough 2 – mediocre 3 – enough If you are sick can you rely on others to help you in SS13 0 – none this need? 1 – not enough 2 – mediocre 3 – enough 258 List people you can depend on in times of need TOTALNAMES How many of these people do you see daily DAILY How many of these people live near to you? NETWORKNEAR How many have you seen in the last two weeks? LAST2WEEKS How many have you seen in the last month? MONTH Ratio of those seen to those on the total list SEENRATIO Category of people seen on list SEENCATEGORY 0 – 0 – 5 people 1 – 6 – 10 people 2 – 10+ people Can you depend on your husband HUSBAND 0 – no 1 – yes Can you depend on your mother-in-law MAMKWE 0 – no 1 – yes Can you depend on your father-in-law BAMKWE 0 – no 1 – yes Can you depend on your in-laws in general INLAWS 0 – no 1 – yes Can you depend on your mother MAMZAZI 0 – no 1 – yes Can you depend on your father BAMZAZI 0 – no 1 – yes Can you depend on your uncle UNCLE 0 – no 1 – yes Can you depend on your aunt AUNTIE 0 – no 1 – yes Can you depend on your brother BROTHER 0 – no 1 – yes Can you depend on your sister SISTER 0 – no 1 – yes Can you depend on your neighbors JIRANI 0 – no 1 – yes Total summed scores on independence INDEPEND questionnaire (I1 – I 11) Sample z-scores for independence INDEPZ Is the independence score above/below mean INDEPZUPDOWN 0 – below 1 – above Summed scores on social support questionnaire SOCSUPPORT Sample z-scores for social support SSZSCORES Is social support score above/below mean SSZCAT 0 – below 1 – above Change in BMI scores monthly BMICHANGE Height change monthly HTCHANGE Rate of height change HR Did you eat goat postpartum? MBUZI 0 – no 1 – yes Did you eat cowfat or butter? FAT 0 – no 1 – yes Did you eat honey? HONEY 0 – no 1 – yes Did you have sugar? SUGAR 0 – no 1 – yes Did you eat chicken? KUKU 0 – no 1 – yes Did you drink milk? MILK 0 – no 1 – yes 259 Total number of postpartum type foods FOODSUMS Percent of total foods listed eaten FOODPERCENT Reciprocal of age 3 months before birth BBAGE3REC Reciprocal of age 1 month after birth PPAGE1REC Kilo change of index in last trimester divided by BBKILO3TO1REC reciprocal of age Kilo change of index in first three months PPKILO1TO3REC postpartum divided by reciprocal of age Having no savings worries me NOSAVINGS 0 – no 1 – yes I worry about the lack of basic needs BASICNEEDS 0 – no 1 – yes Money is a worry MONEY 0 – no 1 – yes Money for medical needs is a worry MEDMONEY 0 – no 1 – yes The lack of food worries me NOFOOD 0 – no 1 – yes My own illness worries me OWNILLNESS 0 – no 1 – yes The illness of others worries me ILLOTHERS 0 – no 1 – yes Marital communication/decision-making worries MARREL 0 – no me 1 – yes I worry about my children WORRYKIDS 0 – no 1 – yes I worry about not having milk MILKS 0 – no 1 – yes Land is a worry for me LAND 0 – no 1 – yes The distance to my farm is a worry DISTFARM 0 – no 1 – yes I worry about STDs STDS 0 – no 1 – yes I worry because I can’t work MOMCANTWORK 0 – no 1 – yes I worry because I don’t have cattle CATTLE 0 – no 1 – yes I worry because there are no employment NOEMPLOYMENT 0 – no opportunities 1 – yes I worry about alcoholics and alcoholism BEER 0 – no 1 – yes I worry because I have no independent plans/ways NOINDEPPLANS 0 – no to get money 1 – yes I worry about family relations FAMREL 0 – no 1 – yes I worry about hard work HARDWORK 0 – no 1 – yes I worry about how hard life is HARDLIFE 0 – no 1 – yes I would like a better house BETTERHOUSE 0 – no 1 – yes 260 I worry about educating my kids EDU 0 – no 1 – yes I worry about violence VIOLENCE 0 – no 1 – yes I worry about taxes TAXES 0 – no 1 – yes The sum of questions in factor 1 FACTOR1SHORT The sum of questions in factor 2 FACTOR2SHORT The sum of questions in factor 3 FACTOR3SHORT The sum of questions in factor 4 FACTOR4SHORT The sum of questions in factor 5 FACTOR5SHORT Total summed scores of RQ1 – RQ25 HSCL25 Sample z-scores for psychosocial stress HSCLZSCORE Was your husband violent during pregnancy? VIOPREGNANT 0 – no 1 – yes Are you afraid your husband is/will be violent? VIOLENTHUSBA 0 – no 1 – somewhat 2 – maybe 3 – yes Is violence a worry in general? VIOTOTAL 0 – yes General violence less women with violent VIOLESSHUS 0 – no husbands 1 – yes Rate of weight gain in last two month LAST2MONKG Rate of weight gain in last month LASTMONKG Ponderal index PONDERAL Distance between index and mother DISTMOM Scolding episode (#) SCOLD Crying episodes (#) CRYEPISODE Minutes of crying CRYMINUTES Comforting episodes (#) COMFORT Number of caretakers present CARETAKERS Is Dad present today? DADPRESENT 0 – no 1 – yes Time out of mothers site WOMOM Total number of time allocation minutes FOLLOWMINS Time without mom as a percentage of total time PERCENTAGE observed Did you eat pumpkin PUMPKIN 0 – no 1 – yes Did you eat uji UJI 0 – no 1 – yes Did you eat ugali UGALI 0 – no 1 – yes Did you eat green vegetables GREEN 0 – no 1 – yes Did you drink milk MILK 0 – no 1 – yes Did you eat kande KANDE 0 – no 1 – yes Did you eat beans BEANS 0 – no 1 – yes Did you eat meat MEAT 0 – no 1 – yes Did you eat honey HONEY 0 – no 261 1 – yes Did you eat onions ONIONS 0 – no 1 – yes Did you eat tomatoes TOMATOE 0 – no 1 – yes Did you drink millet uji MILLETUJI 0 – no 1 – yes Did you eat local fruits LOCALFRUITS 0 – no 1 – yes Did you eat fruit FRUIT 0 – no 1 – yes Did you eat rice RICE 0 – no 1 – yes Did you dink tea TEA 0 – no 1 – yes Did you have cowfat COWFAT 0 – no 1 – yes Did you have mango MANGO 0 – no 1 – yes Did you eat irish potatoes IRISHPOTATOE 0 – no 1 – yes Did you eat sweet potatoes SWEETPOTATOE 0 – no 1 – yes Did you eat chapatti CHAPATI 0 – no 1 – yes Did you have sugar SUGAR 0 – no 1 – yes Did you eat sugarcane SUGARCANE 0 – no 1 – yes Did you eat sunflower seeds SUNSEEDS 0 – no 1 – yes Did you eat bananas BANANAS 0 – no 1 – yes Did you eat fish FISH 0 – no 1 – yes Did you eat soup SUPU 0 – no 1 – yes Did you have blueband butter BLUEBAND 0 – no 1 – yes How many guests were there today? GUESTS Did in-laws visit INLAWPARENTS 0 – no 1 – yes Did inlaw siblings visit INLAWSIBS 0 – no 1 – yes Did neighbors visit NEIGHBOR 0 – no 1 – yes Did others visit OTHERS 0 – no 1 – yes Did relatives visit RELATIVE 0 – no 1 – yes Did children visit CHILDREN 0 – no 1 – yes Did her parents visit HERPARENTS 0 – no 1 – yes Did her siblings visit HERSIBS 0 – no 262 1 – yes Did her aunt visit HERAUNT 0 – no 1 – yes Did her uncle visit HER UNCLE 0 – no 1 – yes Did her cousin visit HERCOUSIN 0 – no 1 – yes Were there workers present WORKERS 0 – no 1 – yes Were there beer drinkers present POMBEPEOPLE 0 – no 1 – yes Were there relatives there working WORKRELATIVE 0 – no 1 – yes Was a witchdoctor there? WITCHDOC 0 – no 1 – yes Did you drink a sugar drink from a shop STOREDRINK 0 – no Did you eat peanuts KARANGA 0 – no 1 – yes Did you eat eggs EGGS 0 – no 1 – yes Did you eat cassava CASSAVA 0 – no 1 – yes Did you feel nauseated while pregnant N1AUSEA 0 – no 1 – yes Did you vomit while pregnant P2UKE 0 – no 1 – yes Did you feel dizzy while pregnant D3IZZY 0 – no 1 – yes Did you have joint pain while pregnant? J4OINT 0 – no 1 – yes Did you have a loss of appetite while pregnant A5PPETITE 0 – no 1 – yes Did you feel weak while pregnant W6EAK 0 – no 1 – yes Did you feel itchy while pregnant I7TCH 0 – no 1 – yes Were there smells that you avoided while pregnant S8MELL 0 – no 1 – yes Did you have heartburn while pregnant H9EARTBURN 0 – no 1 – yes
263 APPENDIX F
AVERAGE RECUMBENT LENGTH AND WEIGHT OF BOYS AND GIRLS IN
STUDY SAMPLE FROM BIRTH THROUGH AGE 74 MONTHS
264
Age, Boys Boys Girls Girls months N Length Weight N Length Weight 0 14 50.4 3.03 29 49.4 3.1 1 10 53.9 4.1 19 51.0 3.6 2 15 55.6 4.1 34 54.3 3.6 3 15 58.6 4.9 23 57.2 4.8 4 13 60.7 5.8 27 58.8 5.5 5 15 61.9 6.5 35 60.6 6.1 6 14 63 7 26 62.2 6.6 7 8 63.3 7.5 25 63.5 6.9 8 2 62.4 7.3 3 65.7 7.7 9 10 11 12 13 14 1 68.8 8.4 15 3 72.0 9.6 16 1 8.2 4 74 9.2 17 5 74.4 9.5 18 1 72.1 8.5 5 76.1 10.5 19 3 72.8 9.2 7 76.5 10.1 20 6 78 10.1 9 78 10.5 21 6 78.4 10.7 9 79.3 10.7 22 5 78.8 10.5 6 79.4 10.6 23 10 80 10.6 12 81 11.1 24 10 81.6 10.7 13 80.7 11.3 25 9 82.7 10.9 11 81.2 11.1 26 9 83.1 11.1 11 83.1 11.4 27 10 82 11.2 16 83.8 11.4 28 11 84.6 11.6 11 84.9 11.6 29 15 85.6 12.1 15 85 11.6 30 14 86.9 12.4 14 85.5 11.7 31 10 86.9 12.3 16 86.7 11.6 32 12 87.5 12 14 87.7 11.9 33 12 87.5 12 14 86.6 11.3 34 7 90 12.8 11 88.2 11.8 35 10 87.5 12 12 88.6 11.7 36 7 89.5 12.5 12 89.1 11.9 37 7 89.1 12.2 7 91.2 12.4 38 6 89.7 12 6 90.7 12 39 4 92.1 13.1 4 89 11.9 40 2 86.4 11.1 3 91.5 12 265
Age, Boys Boys Girls Girls months N Length Weight N Length Weight 41 1 80.3 9.3 3 91 12.4 42 1 82.2 10.2 3 93.1 13.7 43 1 82.3 9.4 1 92.6 13.4 44 1 92.9 13.6 45 2 92.3 13.3 46 2 92.6 13.6 47 2 93.3 14.1 48 3 95.7 14 49 3 97.1 14.2 50 2 98 14.8 51 3 98.7 14.4 52 2 99.8 14.5 53 1 96.7 13.8 1 100.3 13.9 54 1 1 101.9 13.6 55 1 96.9 14.1 1 101.9 13.9 56 1 97 14.1 1 103.4 14.1 57 1 98.7 14.5 1 103.6 14.1 58 1 100.5 14.5 59 1 103.1 15.0 60 1 103.1 15.5 61 1 104.2 15.5 62 1 104.4 15.6 63 1 105.7 15.7 64 1 107.2 15.9 65 1 96.1 11.2 66 1 96.6 11.8 67 1 97.6 12.3 68 1 97.5 13.6 69 1 101.6 13 70 1 102.1 12.6 71 1 102.9 12.7 72 1 102.9 12.9 73 1 103.4 12.9 74 1 103.6 13.6
266 APPENDIX G
PEARSON AND SPEARMAN CORRELATION COEFFICIENTS FOR GROUPS OF
VARIABLES
267 Birth space Birth weight -0.256
Month return work -0.803
Supplement -0.944
HSCL – 25 0.516
Age Birth space -0.372 Wean -0.450
Month return to work -0.581 Supplement -0.309
Birth weight Months of lactation into pregnancy -0.349
Month return to work -0.448
Supplement -0.428
HSCL – 25 -0.319
HSCL – 25 Month return to work -0.555
Supplement -0.606
Supplement Month return to work 0.914
Viototal Birth space 0.211 Birth weight -0.391 Months of lactation into pregnancy 0.053 Weaning age 0.010 Age of mother 0.013
Calf Circumference MUAC Mom 0.783 MUAC Index 0.576 MUAC Newborn 0.853
268
Husband Mamkwe Bamkwe Inlaws Mamzazi Bamzazi Uncle Auntie Brother Sister Jirani Husband 1.00 Mamkwe 0.312 1.00 Bamkwe 0.069 0.538 1.00 Inlaws 0.351 0.588 0.316 1.00 Mamzazi -.216 -0.093 -0.111 0.176 1.00 Bamzazi -.170 0.120 0.378 0.120 0.432 1.00 Uncle 0.216 0.256 0.446 0.035 -0.68 0.358 1.00 Auntie 0.175 -0.031 0.253 -0.040 0.247 0.418 0.388 1.00 Brother 0.223 0.397 0.094 0.299 0.590 0.196 0.200 0.239 1.00 Sister 0.223 -0.018 0.094 -0.239 -0.042 0.330 0.200 0.060 0.063 1.00 Jirani 0.105 -0.074 0.094 0.120 -0.169 -0.018 -.147 0.239 -0.286 -.286 1.00
Housetype WealthcatBuidlingno Housetype 1.00 Wealthcat 0.444 1.00 Buldingno 0.221 0.408 1.00 HSCL – 25 Socsupport Independ HSCL - 25 1.00 Socsupport -0.362 1.00 Viototal Violenthusband Independ -0.342` 0.289 1.00 Viototal 1.00 Violenthusband 0.438 1.000
269
Spearman correlation matrix
NOHELP NOSAVINGS BASICNEEDS MONEY MEDMONEY NOHELP 1.000 NOSAVINGS 0.365 1.000 BASICNEEDS 0.358 0.232 1.000 MONEY 0.000 -0.075 0.202 1.000 MEDMONEY 0.488 0.232 0.302 0.319 1.000 NOFOOD 0.000 0.161 0.322 0.280 0.322 OWNILLNESS 0.264 -0.048 -0.077 0.202 0.301 ILLOTHERS -0.156 -0.086 0.086 0.170 0.310 MARREL 0.313 0.394 0.128 0.379 0.397 WORRYKIDS 0.260 0.542 0.310 -0.017 0.310 MILKS 0.052 0.542 0.310 0.170 0.310 LAND -0.041 -0.113 0.351 0.325 0.173 DISTFARM -0.088 -0.048 -0.077 -0.115 -0.077 STDS -0.126 -0.069 -0.111 0.062 0.160 MOMCANTWORK -0.126 -0.069 0.160 0.289 0.430 CATTLE 0.076 0.105 0.291 0.113 0.291 NOEMPLOYMENT -0.126 0.311 -0.111 -0.165 -0.111 BEER -0.156 -0.086 -0.137 -0.017 -0.137 NOINDEPPLANS 0.000 0.175 -0.160 -0.075 -0.160 FAMREL -0.108 -0.138 0.088 0.059 -0.067 HARDWORK 0.260 -0.086 -0.137 -0.017 -0.137 HARDLIFE -0.088 -0.048 -0.077 -0.115 -0.077 BETTERHOUSE 0.052 -0.086 0.086 -0.017 0.086 EDU -0.088 -0.048 -0.077 0.202 -0.077 VIOLENCE 0.378 -0.069 0.160 0.062 0.430 TAXES 0.264 -0.048 -0.077 0.202 0.301
NOFOOD OWNILLNESS ILLOTHERS MARREL WORRYKIDS NOFOOD 1.000 OWNILLNESS -0.093 1.000 ILLOTHERS 0.037 -0.041 1.000 MARREL 0.033 0.281 -0.147 1.000 WORRYKIDS 0.239 -0.041 -0.073 0.284 1.000 MILKS 0.239 -0.041 0.285 0.284 0.285 LAND 0.263 -0.055 -0.097 -0.023 -0.097 DISTFARM 0.249 -0.023 -0.041 -0.083 -0.041 STDS 0.111 -0.033 -0.059 0.402 -0.059 MOMCANTWORK 0.111 -0.033 0.807 -0.118 -0.059 CATTLE 0.203 0.384 0.155 0.101 -0.107 NOEMPLOYMENT 0.111 -0.033 -0.059 0.142 -0.059 BEER -0.166 -0.041 -0.073 0.068 -0.073 NOINDEPPLANS 0.161 -0.048 -0.086 -0.171 0.228 FAMREL 0.152 -0.066 -0.118 -0.236 -0.118 HARDWORK -0.166 -0.041 -0.073 0.068 -0.073 HARDLIFE -0.093 -0.023 -0.041 -0.083 -0.041 BETTERHOUSE -0.166 -0.041 -0.073 -0.147 -0.073 EDU -0.093 -0.023 -0.041 -0.083 -0.041 VIOLENCE -0.134 0.699 -0.059 0.142 -0.059 TAXES -0.093 1.000 -0.041 0.281 -0.041
270
MILKS LAND DISTFARM STDS MOMCANTWORK MILKS 1.000 LAND -0.097 1.000 DISTFARM -0.041 -0.055 1.000 STDS -0.059 0.266 -0.033 1.000 MOMCANTWORK 0.374 -0.078 -0.033 -0.048 1.000 CATTLE 0.418 0.275 0.384 -0.087 0.231 NOEMPLOYMENT 0.374 -0.078 -0.033 -0.048 -0.048 BEER -0.073 -0.097 -0.041 0.374 -0.059 NOINDEPPLANS -0.086 -0.113 -0.048 -0.069 -0.069 FAMREL -0.118 0.236 -0.066 -0.095 -0.095 HARDWORK -0.073 -0.097 -0.041 -0.059 -0.059 HARDLIFE -0.041 -0.055 -0.023 -0.033 -0.033 BETTERHOUSE -0.073 0.471 -0.041 -0.059 -0.059 EDU -0.041 0.426 -0.023 -0.033 -0.033 VIOLENCE -0.059 0.266 -0.033 -0.048 -0.048 TAXES -0.041 -0.055 -0.023 -0.033 -0.033
CATTLE NOEMPLOYMENT BEER NOINDEPPLANS FAMREL CATTLE 1.000 NOEMPLOYMENT 0.231 1.000 BEER -0.107 -0.059 1.000 NOINDEPPLANS -0.126 -0.069 -0.086 1.000 FAMREL 0.008 -0.095 0.375 0.295 1.000 HARDWORK -0.107 -0.059 -0.073 -0.086 -0.118 HARDLIFE -0.061 -0.033 -0.041 -0.048 0.351 BETTERHOUSE 0.155 -0.059 -0.073 -0.086 0.129 EDU -0.061 -0.033 -0.041 -0.048 -0.066 VIOLENCE 0.549 -0.048 -0.059 -0.069 0.203 TAXES 0.384 -0.033 -0.041 -0.048 -0.066
HARDWORK HARDLIFE BETTERHOUSE EDU VIOLENCE HARDWORK 1.000 HARDLIFE -0.041 1.000 BETTERHOUSE -0.073 -0.041 1.000 EDU -0.041 -0.023 0.564 1.000 VIOLENCE -0.059 -0.033 0.374 -0.033 1.000 TAXES -0.041 -0.023 -0.041 -0.023 0.699
TAXES TAXES 1.000
Number of observations: 44
271